{"id":13444336,"url":"https://github.com/uzh-rpg/event-based_vision_resources","last_synced_at":"2026-01-26T12:34:38.385Z","repository":{"id":38361640,"uuid":"95533189","full_name":"uzh-rpg/event-based_vision_resources","owner":"uzh-rpg","description":"Event-based Vision Resources. Community effort to collect knowledge on event-based vision technology (papers, workshops, datasets, code, videos, etc)","archived":false,"fork":false,"pushed_at":"2025-11-17T08:58:53.000Z","size":2603,"stargazers_count":3373,"open_issues_count":0,"forks_count":715,"subscribers_count":176,"default_branch":"master","last_synced_at":"2025-11-17T10:24:10.487Z","etag":null,"topics":[],"latest_commit_sha":null,"homepage":"","language":null,"has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":null,"status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/uzh-rpg.png","metadata":{"files":{"readme":"README.md","changelog":null,"contributing":"Contributing.md","funding":null,"license":null,"code_of_conduct":null,"threat_model":null,"audit":null,"citation":null,"codeowners":null,"security":null,"support":null,"governance":null,"roadmap":null,"authors":null,"dei":null,"publiccode":null,"codemeta":null,"zenodo":null,"notice":null,"maintainers":null,"copyright":null,"agents":null,"dco":null,"cla":null}},"created_at":"2017-06-27T08:00:43.000Z","updated_at":"2025-11-17T08:58:58.000Z","dependencies_parsed_at":"2023-09-24T16:16:45.209Z","dependency_job_id":"ddff341b-3c86-4567-995a-be4b6f0e63eb","html_url":"https://github.com/uzh-rpg/event-based_vision_resources","commit_stats":null,"previous_names":[],"tags_count":0,"template":false,"template_full_name":null,"purl":"pkg:github/uzh-rpg/event-based_vision_resources","repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/uzh-rpg%2Fevent-based_vision_resources","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/uzh-rpg%2Fevent-based_vision_resources/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/uzh-rpg%2Fevent-based_vision_resources/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/uzh-rpg%2Fevent-based_vision_resources/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/uzh-rpg","download_url":"https://codeload.github.com/uzh-rpg/event-based_vision_resources/tar.gz/refs/heads/master","sbom_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/uzh-rpg%2Fevent-based_vision_resources/sbom","scorecard":{"id":716026,"data":{"date":"2025-08-11","repo":{"name":"github.com/uzh-rpg/event-based_vision_resources","commit":"260acd1b2f78e29c5fef398069b656f8609ab20c"},"scorecard":{"version":"v5.2.1-40-gf6ed084d","commit":"f6ed084d17c9236477efd66e5b258b9d4cc7b389"},"score":5.4,"checks":[{"name":"Dangerous-Workflow","score":-1,"reason":"no workflows found","details":null,"documentation":{"short":"Determines if the project's GitHub Action workflows avoid dangerous patterns.","url":"https://github.com/ossf/scorecard/blob/f6ed084d17c9236477efd66e5b258b9d4cc7b389/docs/checks.md#dangerous-workflow"}},{"name":"Maintained","score":10,"reason":"30 commit(s) and 0 issue activity found in the last 90 days -- score normalized to 10","details":null,"documentation":{"short":"Determines if the project is \"actively maintained\".","url":"https://github.com/ossf/scorecard/blob/f6ed084d17c9236477efd66e5b258b9d4cc7b389/docs/checks.md#maintained"}},{"name":"Binary-Artifacts","score":10,"reason":"no binaries found in the repo","details":null,"documentation":{"short":"Determines if the project has generated executable (binary) artifacts in the source repository.","url":"https://github.com/ossf/scorecard/blob/f6ed084d17c9236477efd66e5b258b9d4cc7b389/docs/checks.md#binary-artifacts"}},{"name":"Code-Review","score":6,"reason":"Found 11/17 approved changesets -- score normalized to 6","details":null,"documentation":{"short":"Determines if the project requires human code review before pull requests (aka merge requests) are merged.","url":"https://github.com/ossf/scorecard/blob/f6ed084d17c9236477efd66e5b258b9d4cc7b389/docs/checks.md#code-review"}},{"name":"Packaging","score":-1,"reason":"packaging workflow not detected","details":["Warn: no GitHub/GitLab publishing workflow detected."],"documentation":{"short":"Determines if the project is published as a package that others can easily download, install, easily update, and uninstall.","url":"https://github.com/ossf/scorecard/blob/f6ed084d17c9236477efd66e5b258b9d4cc7b389/docs/checks.md#packaging"}},{"name":"Token-Permissions","score":-1,"reason":"No tokens found","details":null,"documentation":{"short":"Determines if the project's workflows follow the principle of least privilege.","url":"https://github.com/ossf/scorecard/blob/f6ed084d17c9236477efd66e5b258b9d4cc7b389/docs/checks.md#token-permissions"}},{"name":"Pinned-Dependencies","score":-1,"reason":"no dependencies found","details":null,"documentation":{"short":"Determines if the project has declared and pinned the dependencies of its build process.","url":"https://github.com/ossf/scorecard/blob/f6ed084d17c9236477efd66e5b258b9d4cc7b389/docs/checks.md#pinned-dependencies"}},{"name":"CII-Best-Practices","score":0,"reason":"no effort to earn an OpenSSF best practices badge detected","details":null,"documentation":{"short":"Determines if the project has an OpenSSF (formerly CII) Best Practices Badge.","url":"https://github.com/ossf/scorecard/blob/f6ed084d17c9236477efd66e5b258b9d4cc7b389/docs/checks.md#cii-best-practices"}},{"name":"Security-Policy","score":0,"reason":"security policy file not detected","details":["Warn: no security policy file detected","Warn: no security file to analyze","Warn: no security file to analyze","Warn: no security file to analyze"],"documentation":{"short":"Determines if the project has published a security policy.","url":"https://github.com/ossf/scorecard/blob/f6ed084d17c9236477efd66e5b258b9d4cc7b389/docs/checks.md#security-policy"}},{"name":"Vulnerabilities","score":10,"reason":"0 existing vulnerabilities detected","details":null,"documentation":{"short":"Determines if the project has open, known unfixed vulnerabilities.","url":"https://github.com/ossf/scorecard/blob/f6ed084d17c9236477efd66e5b258b9d4cc7b389/docs/checks.md#vulnerabilities"}},{"name":"License","score":0,"reason":"license file not detected","details":["Warn: project does not have a license file"],"documentation":{"short":"Determines if the project has defined a license.","url":"https://github.com/ossf/scorecard/blob/f6ed084d17c9236477efd66e5b258b9d4cc7b389/docs/checks.md#license"}},{"name":"Signed-Releases","score":-1,"reason":"no releases found","details":null,"documentation":{"short":"Determines if the project cryptographically signs release artifacts.","url":"https://github.com/ossf/scorecard/blob/f6ed084d17c9236477efd66e5b258b9d4cc7b389/docs/checks.md#signed-releases"}},{"name":"Fuzzing","score":0,"reason":"project is not fuzzed","details":["Warn: no fuzzer integrations found"],"documentation":{"short":"Determines if the project uses fuzzing.","url":"https://github.com/ossf/scorecard/blob/f6ed084d17c9236477efd66e5b258b9d4cc7b389/docs/checks.md#fuzzing"}},{"name":"Branch-Protection","score":-1,"reason":"internal error: error during branchesHandler.setup: internal error: githubv4.Query: Resource not accessible by integration","details":null,"documentation":{"short":"Determines if the default and release branches are protected with GitHub's branch protection settings.","url":"https://github.com/ossf/scorecard/blob/f6ed084d17c9236477efd66e5b258b9d4cc7b389/docs/checks.md#branch-protection"}},{"name":"SAST","score":0,"reason":"SAST tool is not run on all commits -- score normalized to 0","details":["Warn: 0 commits out of 24 are checked with a SAST tool"],"documentation":{"short":"Determines if the project uses static code analysis.","url":"https://github.com/ossf/scorecard/blob/f6ed084d17c9236477efd66e5b258b9d4cc7b389/docs/checks.md#sast"}}]},"last_synced_at":"2025-08-22T09:41:01.688Z","repository_id":38361640,"created_at":"2025-08-22T09:41:01.688Z","updated_at":"2025-08-22T09:41:01.688Z"},"host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":286080680,"owners_count":28778293,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2026-01-26T11:46:04.308Z","status":"ssl_error","status_checked_at":"2026-01-26T11:46:02.664Z","response_time":59,"last_error":"SSL_connect returned=1 errno=0 peeraddr=140.82.121.5:443 state=error: unexpected eof while reading","robots_txt_status":"success","robots_txt_updated_at":"2025-07-24T06:49:26.215Z","robots_txt_url":"https://github.com/robots.txt","online":false,"can_crawl_api":true,"host_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub","repositories_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories","repository_names_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repository_names","owners_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners"}},"keywords":[],"created_at":"2024-07-31T04:00:20.240Z","updated_at":"2026-01-26T12:34:38.359Z","avatar_url":"https://github.com/uzh-rpg.png","language":null,"funding_links":[],"categories":["Uncategorized","相机技术\u0026参数","Others","Footnotes","Optical Flow","Review","Lecture \u0026 Tutorials \u0026 Text Book"],"sub_categories":["Uncategorized","SynSense","Special Device"],"readme":"# Event-based Vision Resources\n\n## \u003ca href=\"https://joint-research-centre.ec.europa.eu/events/innovative-neuromorphic-vision-sensors-invisions-workshop-2026-02-05_en\"\u003e Innovative Neuromorphic Vision Sensors (INVISIONS) workshop, 2026.\u003c/a\u003e Feb 5th-6th.\n## \u003ca href=\"https://ieee-cas.org/files/ieeecass/2025-08/JETCAS_CFP_2026Q3.pdf\"\u003e Neuromorphic Computing and Sensing Meets Extended Reality — IEEE JETCAS Special Issue \"Circuits and Systems for Extended Reality\" Call for Papers. \u003c/a\u003e Paper submission until March 2nd 2026.\n## \u003ca href=\"https://edpr.iit.it/events/2026-evs\"\u003e EVS: Event Vision School 2026.\u003c/a\u003e May 17-23th, Arenzano (Italy).\n## \u003ca href=\"https://eventbasedvision.github.io/EVGEN2026/\"\u003e WACV 2026 EVGEN: Event-based Vision in the Era of Generative AI.\u003c/a\u003e March 2026, Tucosn (USA). Paper submission until Dec 7th 2025.\n## \u003ca href=\"https://spie.org/photonics-west/event/vision-tech-event-based-session-neuromorphic-sensing-in-motion-from-event-based-vision-to-adaptive-intelligence/7101335\"\u003e SPIE Photonics West. Vision Tech Forum. Neuromorphic Sensing in Motion: From Event-Based Vision to Adaptive Intelligence,\u003c/a\u003e Jan. 21, 2026 \n## \u003ca href=\"https://www.neuropac.info/\"\u003eNeuroPAC\u003c/a\u003e\n## \u003ca href=\"https://hylz-2019.github.io/Neuro_Vision_Map/map.html\"\u003eMap of event-based institutions (from papers)\u003c/a\u003e\n[![Neuro Vision Map](docs/img/map_of_event_based_institutions.jpg)](https://hylz-2019.github.io/Neuro_Vision_Map/map.html)\n\n- [Contribute to the above map](https://github.com/HYLZ-2019/Neuro_Vision_Map)\n\n## Table of Contents:\n- [Survey paper](#survey_paper)\n- [Workshops](#workshops)\n- [Devices and Manufacturers](#devices)\n- [Companies working on Event-based Vision](#companies_sftwr)\n- [Neuromorphic Systems](#neuromorphic-systems)\n- [Review papers](#reviewpapers)\n    - [Bio-inspiration](#reviewpapers-bio)\n    - [Algorithms, Applications](#reviewpapers-algs)\n\n- [Applications / Algorithms](#algorithms)\n    - [Feature Detection and Tracking](#feature-detection)\n        - [Corners](#corner-detection)\n        - [Particles in fluids](#particle-detection)\n        - [Eye Tracking](#eye_tracking)\n    - [Optical Flow Estimation](#optical-flow-estimation)\n        - [Scene Flow Estimation](#scene-flow-estimation)\n    - [Reconstruction of Visual Information](#visualization)\n        - [Intensity-Image Reconstruction](#image-reconstruction)\n        - [Video Synthesis](#video-synthesis)\n        - [Image super-resolution](#super-resolution)\n        - [Joint/guided filtering](#joint-filtering)\n        - [Tone mapping](#tone-mapping)\n        - [Visual Stabilization](#visual-stabilization)\n        - [Polarization Reconstruction](#polarization-reconstruction)\n    - [Depth Estimation (3D Reconstruction)](#depth-estimation)\n        - [Monocular](#depth-mono)\n        - [Monocular Depth Estimation using Structured Light](#depth-mono-active)\n        - [Monocular Object Reconstruction](#object-mono)\n        - [Stereo](#depth-stereo)\n        - [Stereo Depth Estimation using Structured Light](#depth-stereo-active)\n        - [Stereoscopic panoramic imaging](#depth-stereo-pano)\n        - [Events and LiDAR](#event-lidar-fusion)\n    - [SLAM (Simultaneous Localization And Mapping)](#slam)\n        - [Localization, Ego-motion estimation](#slam-localization)\n        - [Visual Odometry](#visual-odometry)\n        - [Visual-Inertial Odometry](#visual-inertial)\n    - [Segmentation](#segmentation)\n        - [Object Segmentation](#object-segmentation)\n        - [Motion Segmentation](#motion-segmentation)\n    - [Pattern recognition](#pattern-recognition)\n        - [Object Recognition](#object-recognition)\n        - [Gesture Recognition](#gesture-recognition)\n        - [Representation / Feature Extraction](#learning-representation-features)\n        - [Regression Tasks](#learning-regression)\n        - [Learning Methods / Frameworks](#learning-methods-frameworks)\n    - [Signal Processing](#signal_processing)\n        - [Event Denoising](#denoising)\n        - [Compression](#compression)\n        - [Event Downsampling](#downsampling)\n    - [Control](#control)\n    - [Obstacle Avoidance](#obstacle_avoidance)\n    - [Space Applications](#space)\n    - [Tactile Sensing Applications](#tactile_sensing)\n    - [Object Pose Estimation](#object_pose_estimation)\n        - [Human Pose Estimation](#human_pose_estimation)\n        - [Hand Pose Estimation](#hand_pose_estimation)\n    - [Indoor Lighting Estimation](#indoor_lighting_estimation)\n    - [Data Encryption](#data_encription)\n    - [Nuclear Verification](#nuclear_verification)\n    - [Optical Communication](#optical_communication)\n    - [Animal Behavior Monitoring](#animal_monitoring)\n    - [Optical Applications](#optical_applications)\n      - [Auto-focus](#auto_focus)\n      - [Auto-exposure](#auto_exposure)\n      - [Speckle Analysis](#speckle_analysis)\n      - [Interferometry or Holography](#interferometry_or_holography)\n      - [Wavefront sensing](#wavefront_sensing)\n      - [Optical super-resolution](#super_resolution_imaging)\n      - [Schlieren imaging](#schlieren_imaging)\n      - [Event-Based Image Velocimetry (EBIV)](#event-based-image-velocimetry)\n    - [Driver Monitoring System](#driver_monitoring_system)\n      - [Multi-tasking networks: Face, Head Pose \u0026 Eye Gaze estimation](#DMS)\n      - [Drowsiness or Yawn](#Drwosiness_or_yawn)\n      - [Distraction](#distraction_detecton)\n    - [Face Alignment and Landmark Detection](#face-alignment-landmarking)\n    - [Visual Voice Activity Detection](#voice-activity-detection)\n      \n\n- [Simulators and Emulators](#simulators-emulators)\n- [Synthetic Data Generators](#synthetic-data-generators)\n- [Datasets](#datasets)\n- [Software](#software)\n    - [Drivers](#drivers)\n    - [Synchronization](#synchronization)\n    - [Lens Calibration](#calibration)\n    - [Algorithms](#software-algorithms)\n    - [Utilities](#software-utilities)\n\n- [Neuromorphic Processors and Platforms](#processors-platforms)\n- [Courses](#teaching)\n- [Theses and Dissertations](#theses)\n    - [Dissertations](#theses-phd)\n    - [Master's Theses](#theses-master)\n- [People / Organizations](#people)\n- [EETimes articles](#press-eetimes)\n- [Contributing](#contributing)\n\n___\n\u003cbr\u003e\n\n\u003ca name=\"survey_paper\"\u003e\u003c/a\u003e\n# Survey paper\n- \u003ca name=\"Gallego20tpami\"\u003e\u003c/a\u003eGallego, G., Delbruck, T., Orchard, G., Bartolozzi, C., Taba, B., Censi, A., Leutenegger, S., Davison, A., Conradt, J., Daniilidis, K., Scaramuzza, D.,  \n**_[Event-based Vision: A Survey](http://rpg.ifi.uzh.ch/docs/EventVisionSurvey.pdf)_**,  \nIEEE Trans. Pattern Anal. Machine Intell. (TPAMI), 44(1):154-180, Jan. 2022.\n\n\n\u003ca name=\"workshops\"\u003e\u003c/a\u003e\n# Workshops\n- [EVS 2026: Event Vision School 2026](https://edpr.iit.it/events/2026-evs)\n- [WACV 2026 EVGEN: 2nd Worksgop on Event-based Vision in the Era of Generative AI - Transforming Perception and Visual Innovation](https://eventbasedvision.github.io/EVGEN2026/)\n- [IROS 2025 Workshop on Event-Based Vision. And Stereo SLAM Challenge](https://sites.google.com/view/neurobots2025)\n- [IROS 2025 Workshop on Neuromorphic Perception for Real World Robotics (NeuRobots 2025)](https://sites.google.com/view/iros-2024-workshop)\n- [ICCV 2025 2nd Workshop on Neuromorphic Vision (NeVi)](https://sites.google.com/view/nevi-2025/)\n- [DSP 2025 Special Session on Event-based Vision: “Processing the Neuromorphic Signal: Event-based Vision and Applications”](https://2025.ic-dsp.org/special-session-4/)\n- [2025 Telluride Neuromorphic Cognition Engineering Workshop](https://sites.google.com/view/telluride-2025/home)\n- [IEEE T-RO Special Collection on Event-based Vision for Robotics, 2025](https://www.ieee-ras.org/publications/t-ro/special-issues/event-based-vision-for-robotics)\n- [CVPR 2025 Fifth International Workshop on Event-based Vision](https://tub-rip.github.io/eventvision2025)\n- [WACV 2025 EVGEN: Event-based Vision in the Era of Generative AI - Transforming Perception and Visual Innovation](https://eventbasedvision.github.io/EVGEN2025/)\n- [IROS 2024 Workshop on Embodied Neuromorphic AI for Robotic Perception and Control](https://sites.google.com/view/iros-2024-workshop)\n- [ECCV 2024 Workshop on Neuromorphic Vision (NeVi)](https://sites.google.com/view/nevi2024), **[Slides](https://sites.google.com/view/nevi2024/program)**\n- [ECCV 2024 1st Workshop on Neural Fields Beyond Conventional Cameras](https://neural-fields-beyond-cams.github.io/)\n- [Caméra à événements appliquée à la robotique, Sorbonne University, Paris (Nov. 16th, 2023)](https://tub-rip.github.io/eventvision2023/slides/2023-11_Workshop_event_cameras_Sorbonne.pdf)\n- [CVPR 2023 Fourth International Workshop on Event-based Vision](https://tub-rip.github.io/eventvision2023), **[Videos](https://www.youtube.com/playlist?list=PLeXWz-g2If96iotpzgBNNTr9VA6hG-LLK)**\n- [IEEE Embedded Vision Workshop Series](https://embeddedvisionworkshop.wordpress.com), with focus on Biologically-inspired vision and embedded systems.\n- [IISW 2023 Int. Image Sensor Workshop](https://imagesensors.org/2023-international-image-sensor-workshop/)\n- [MFI 2022 First Neuromorphic Event Sensor Fusion Workshop](https://sites.google.com/view/eventsensorfusion2022/home) with videos incl. _Event Sensor Fusion Jeopardy_ game - Virtual. **[Videos](https://youtube.com/playlist?list=PLVtZ8f-q0U5gXhjN4inwWZi66bp5vp-lN)**\n- [tinyML Neuromorphic Engineering Forum](https://www.tinyml.org/event/tinyml-neuromorphic-engineering-forum/) - Virtual, 2022. **[Videos](https://www.youtube.com/playlist?list=PLeisuBi-nfBM5HayCqF4KMBaJciV5UkLX)**\n- [ICCV 2021 Tutorial. Introduction to Event Detection Cameras](https://tub-rip.github.io/eventvision2021/slides/ICCV2021Tutorial.pdf)\n- [CVPR 2021 Third International Workshop on Event-based Vision](https://tub-rip.github.io/eventvision2021) - Virtual. **[Videos](https://www.youtube.com/playlist?list=PLeXWz-g2If95mjNpA-y-WIoDaoB8WtmE7)**\n- [ICRA 2020 Workshop on Unconventional Sensors in Robotics](https://sites.google.com/view/unconventional-sensors) - Virtual. **[Videos](https://www.youtube.com/playlist?list=PLtW5yHT6tQuD4sLzkldzZEyQ4hz77K64-)**\n- [Neuro-Inspired Computational Elements (NICE) Workshop Series](https://niceworkshop.org/nice-2019/). **[Videos](https://www.youtube.com/channel/UCKTLpjY9e8cMK12d2-Z-usA)**\n- [Capo Caccia Workshops toward Cognitive Neuromorphic Engineering](http://capocaccia.iniforum.ch/).\n- [The Telluride Neuromorphic Cognition Engineering Workshops](https://tellurideneuromorhic.org). **[Videos](https://sites.google.com/view/telluride2020/about-workshop/videos)**, Telluride 2020 (Online): **[Videos](https://www.youtube.com/playlist?list=PLG-iqBTOyCO5NAbqbsHPPnL9h35z0ooSE)**, **[Slides](https://drive.google.com/drive/folders/1lmUSjZoDb7yc_HO9xw0M5J4fIGRIfu_u)**\n- [CVPR 2019 Second International Workshop on Event-based Vision and Smart Cameras](http://rpg.ifi.uzh.ch/CVPR19_event_vision_workshop.html). **[Videos](https://www.youtube.com/playlist?list=PLeXWz-g2If97iGiuBHmnW8IFIxwvSeCHx)**\n- [IROS 2018 Unconventional Sensing and Processing for Robotic Visual Perception](https://www.jmartel.net/irosws-home).\n- [ICRA 2017 First International Workshop on Event-based Vision](http://rpg.ifi.uzh.ch/ICRA17_event_vision_workshop.html). **[Videos](https://www.youtube.com/playlist?list=PLeXWz-g2If94k8mw6GcKU5C9PUgM1sK0U)**\n- [IROS 2015 Event-Based Vision for High-Speed Robotics (slides)](http://www.rit.edu/kgcoe/iros15workshop/papers/IROS2015-WASRoP-Invited-04-slides.pdf), Workshop on Alternative Sensing for Robot Perception.\n- [ICRA 2015 Workshop on Innovative Sensing for Robotics](http://innovative-sensing.mit.edu/), with a focus on Neuromorphic Sensors.\n    \n\n\u003ca name=\"devices\"\u003e\u003c/a\u003e\n# Devices \u0026 Companies Manufacturing them\n- **DVS (Dynamic Vision Sensor)**: Lichtsteiner, P., Posch, C., and Delbruck, T., *[A 128x128 120dB 15μs latency asynchronous temporal contrast vision sensor](http://doi.org/10.1109/JSSC.2007.914337)*, IEEE J. Solid-State Circuits, 43(2):566-576, 2008. [PDF](https://www.ini.uzh.ch/~tobi/wiki/lib/exe/fetch.php?media=lichtsteiner_dvs_jssc08.pdf)\n    - [Product page at iniVation](https://inivation.com/dvs/). [**Buy a DVS**](https://inivation.com/buy/)\n    - [Product specifications](https://inivation.com/support/product-specifications/)    \n    - [User guide](https://inivation.github.io/inivation-docs/Hardware%20user%20guides/User_guide_-_DVS128.html)\n    - [Introductory videos about the DVS technology](https://inivation.com/dvs/videos/)\n    - [iniVation AG](https://inivation.com/) invents, produces and sells neuromorphic technologies with a special focus on event-based vision into *business*. [Slides](http://rpg.ifi.uzh.ch/docs/ICRA17workshop/Jakobsen.pdf) by [S. E. Jakobsen](https://inivation.com/company/), board member of iniVation.\n    - [Event Cameras - Tutorial - Tobi Delbruck, version 4](https://youtu.be/Th4TM4SsFGY)\n- **Samsung's DVS**\n    - [Slides](http://rpg.ifi.uzh.ch/docs/CVPR19workshop/CVPRW19_Eric_Ryu_Samsung.pdf) and [Video](https://youtu.be/7fAPckjQSGE) by [Hyunsurk Eric Ryu](https://www.linkedin.com/in/hyunsurk-eric-ryu-82745712), Samsung Electronics  (2019).\n    - Suh et al., *[A 1280×960 Dynamic Vision Sensor with a 4.95-μm Pixel Pitch and Motion Artifact Minimization](https://doi.org/10.1109/ISCAS45731.2020.9180436)*, IEEE Int. Symp. Circuits and Systems (ISCAS), 2020.    \n    - Son, B., et al., *[A 640×480 dynamic vision sensor with a 9µm pixel and 300Meps address-event representation](https://doi.org/10.1109/ISSCC.2017.7870263)*, IEEE Int. Solid-State Circuits Conf. (ISSCC), 2017, pp. 66-67.\n    - [SmartThings Vision](https://www.samsung.com/se/smartthings/smartthings-vision-u999/) commercial product for home monitoring. [in Australia](https://www.samsung.com/au/smart-home/smartthings-vision-u999/)\n    - [Paper at IEDM 2019](#Park19iedm), about low-latency applications using Samsung's VGA DVS.\n- **HVS** (Hybrid Vision Sensors) like  **ATIS**, **DAVIS**, **CDAVIS**, and other HVS that output brightness change events and intensity frames, either mono or color\n    - **ATIS** [(Asynchronous Time-based Image Sensor), Posch et al. JSSC 2011](#Posch11jssc),\n      *A QVGA 143 dB Dynamic Range Frame-Free PWM Image Sensor With Lossless Pixel-Level Video Compression and Time-Domain CDS*.\n    - **DAVIS (Dynamic and Active Pixel Vision Sensor)**: Brandli, C., Berner, R., Yang, M., Liu, S.-C., Delbruck, T., *[A 240x180 130 dB 3 µs Latency Global Shutter Spatiotemporal Vision Sensor](https://doi.org/10.1109/JSSC.2014.2342715)*, IEEE J. Solid-State Circuits, 49(10):2333-2341, 2014. [PDF](https://drive.google.com/file/d/0BzvXOhBHjRhea3RrelA1V0RKVWM/view)\n        - [Product page at iniVation](https://inivation.com/dvs/).  [**Buy a DAVIS**](https://inivation.com/buy/)\n        - [Product specifications](https://inivation.com/support/product-specifications/)\n        - [User guide](https://inivation.github.io/inivation-docs/Hardware%20user%20guides/User_guide_-_DAVIS240.html)\n    - **DAVIS346**: Taverni, G; Paul Moeys, D; Li, C; Cavaco, C; Motsnyi, V; San Segundo Bello, D; Delbruck, T., *[Front and Back Illuminated Dynamic and Active Pixel Vision Sensors Comparison](http://dx.doi.org/10.1109/TCSII.2018.2824899)*, IEEE Trans. Circuits Syst. Express Briefs, 2018\n    - **CDAVIS HVS**: Li, C., Brandli, C., Berner, R., Liu, H., Yang, M., Liu, S.-C., Delbruck, T., *[An RGBW color VGA rolling and global shutter dynamic and active-pixel vision sensor](https://www.imagesensors.org/Past%20Workshops/2015%20Workshop/2015%20Papers/Sessions/Session_13/13-05_Li_Delbruck.pdf)*, Int. Image Sensors Worskhop, 2015.\n        - Prototype only \n    - **SDAVIS192**: Moeys, D. P., Corradi, F., Li, C., Bamford, S. A., Longinotti, L., Voigt, F. F., Berry, S., Taverni, G., Helmchen, F., Delbruck, T., *[A Sensitive Dynamic and Active Pixel Vision Sensor for Color or Neural Imaging Applications](https://doi.org/10.1109/TBCAS.2017.2759783)*, IEEE Trans. Biomed. Circuits Syst. 12(1):123-136 2018.\n        - Prototype only\n    - **Omnivision HVS**: Guo et al, [A 3-Wafer-Stacked Hybrid 15MPixel CIS + 1 MPixel EVS with 4.6GEvent/s Readout, In-Pixel TDC and On-Chip ISP and ESP Function](http://dx.doi.org/10.1109/isscc42615.2023.10067476), ISSCC, (2023).\n        - Prototype, commercially n.a. \n    - **Sony HVS**: Kodama et al., [1.22μm 35.6Mpixel RGB Hybrid Event-Based Vision Sensor with 4.88μm-Pitch Event Pixels and up to 10K Event Frame Rate by Adaptive Control on Event Sparsity](http://dx.doi.org/10.1109/ISSCC42615.2023.10067520), ISSCC (2023)\n        - Prototype only, commercially n.a. \n- [**Insightness's Silicon Eye**](https://youtu.be/Y0mIb_MehK8) QVGA event sensor.\n    - [The Silicon Eye Technology](http://www.insightness.com/?p=361)\n    - [Slides](http://rpg.ifi.uzh.ch/docs/CVPR19workshop/CVPRW19_Insightness.pdf) and [Video](https://youtu.be/9IJwF9xYEoU) by [Stefan Isler](http://www.insightness.com/#team) (2019).\n    - [Slides](http://rpg.ifi.uzh.ch/docs/ICRA17workshop/Insightness.pdf) and [Video](https://youtu.be/6YyOW6DDGKw) by [Christian Brandli](http://www.insightness.com/#team), CEO and co-founder of Insightness (2017).\n- [**PROPHESEE’s Metavision Sensor**](https://www.prophesee.ai/event-based-sensor-packaged/) and [**Software**](https://www.prophesee.ai/metavision-intelligence/)\n    - **ATIS** \u003ca name=\"Posch11jssc\"\u003e\u003c/a\u003e (Asynchronous Time-based Image Sensor): Posch, C., Matolin, D., Wohlgenannt, R. (2011). *[A QVGA 143 dB Dynamic Range Frame-Free PWM Image Sensor With Lossless Pixel-Level Video Compression and Time-Domain CDS](http://doi.org/10.1109/JSSC.2010.2085952)*, IEEE J. Solid-State Circuits, 46(1):259-275, 2011. [YouTube](https://youtu.be/YQ8rT9Harb4), [YouTube](https://youtu.be/3Wiw8LA8hLs)\n    - Prophesee Gen4 is described in: Finateu et al., *[A 1280×720 Back-Illuminated Stacked Temporal Contrast Event-Based Vision Sensor with 4.86μm Pixels, 1.066GEPS Readout, Programmable Event-Rate Controller and Compressive Data-Formatting Pipeline](https://doi.org/10.1109/ISSCC19947.2020.9063149)*, IEEE Int. Solid-State Circuits Conf. (ISSCC), 2020, pp. 112-114.\n    - [**Buy a Prophesee packaged sensor VGA**](https://www.prophesee.ai/event-based-sensor-packaged)\n    - [Prophesee Cameras Specifications](https://www.prophesee.ai/event-based-evaluation-kits/)\n    - What is event-based vision and sample applications, [YouTube](https://www.youtube.com/watch?v=MjX3z-6n3iA)\n    - [Download free or buy Metavision software ](https://www.prophesee.ai/metavision-intelligence/)\n    - [Documentation and tutorials](https://docs.prophesee.ai/)\n    - [Knowledge Base](https://support.prophesee.ai/portal/en/kb/prophesee-1) and [Community Forum](https://support.prophesee.ai/portal/en/community/forum)\n- [**SONY's explanation of Event-based Vision Sensor (EVS) Technolgy**](https://www.sony-semicon.com/en/technology/industry/evs.html)\n- [**CelePixel**](http://www.celepixel.com/), Shanghai. CeleX-V: the first 1 Mega-pixel event-camera sensor.\n- **Sensitive DVS (sDVS)**\n    - All are prototypes, commerically n.a.\n    - Leñero-Bardallo, J. A., Serrano-Gotarredona, T., Linares-Barranco, B., *[A 3.6us Asynchronous Frame-Free Event-Driven Dynamic-Vision-Sensor](https://doi.org/10.1109/JSSC.2011.2118490)*,  IEEE J. of Solid-State Circuits, 46(6):1443-1455, 2011.\n    - Serrano-Gotarredona, T. and Linares-Barranco, B., *[A 128x128 1.5% Contrast Sensitivity 0.9% FPN 3us Latency 4mW Asynchronous Frame-Free Dynamic Vision Sensor Using Transimpedance Amplifiers](https://doi.org/10.1109/JSSC.2012.2230553)*,  IEEE J. Solid-State Circuits, 48(3):827-838, 2013.\n    - **SDAVIS192**: Moeys, D. P., Corradi, F., Li, C., Bamford, S. A., Longinotti, L., Voigt, F. F., Berry, S., Taverni, G., Helmchen, F., Delbruck, T., *[A Sensitive Dynamic and Active Pixel Vision Sensor for Color or Neural Imaging Applications](https://doi.org/10.1109/TBCAS.2017.2759783)*, IEEE Trans. Biomed. Circuits Syst. 12(1):123-136 2018.\n    - **SciDVS**: Graca, R., Zhou, S., McReynolds, B., Delbruck, T., *[SciDVS: A Scientific Event Camera with 1.7% Temporal Contrast Sensitivity at 0.7 lux](https://doi.org/10.1109/ESSERC62670.2024.10719521)*, ESSERC, (2024).\n- **DLS (Dynamic Line Sensor)**: Posch, C., Hofstaetter, M., Matolin, D., Vanstraelen, G., Schoen, P., Donath, N., and Litzenberger, M., *[A dual-line optical transient sensor with on-chip precision time-stamp generation](https://doi.org/10.1109/ISSCC.2007.373513)*, IEEE Int. Solid-State Circuits Conf. - Digest of Technical Papers, Lisbon Falls, MN, US, 2007.\n    - [Fact sheet at AIT](https://www.ait.ac.at/fileadmin/mc/digital_safety_security/downloads/Factsheet_-_Linescan-Chip_DLS_en.pdf).\n- **LWIR DVS**: Posch, C., Matolin, D., Wohlgenannt, R., Maier, T., Litzenberger, M., *[A Microbolometer Asynchronous Dynamic Vision Sensor for LWIR](https://doi.org/10.1109/JSEN.2009.2020658)*, IEEE Sensors Journal, 9(6):654-664, 2009.\n    - Prototype, commercially n.a.\n- **Smart DVS (GAEP)**: Posch, C., Hoffstaetter, M., Schoen, P., *[A SPARC-compatible general purpose Address-Event processor with 20-bit 10ns-resolution asynchronous sensor data interface in 0.18um CMOS](https://doi.org/10.1109/ISCAS.2010.5537575)*, IEEE Int. Symp. Circuits and Systems (ISCAS), 2010.\n    - Prototype, commercially n.a.\n- **PDAVIS (Polarization Event Camera)**:\n  - Prototype, commercially n.a.\n  - [Bio-inspired Polarization Event Camera](http://arxiv.org/abs/2112.01933), arXiv [cs.CV] (2021) [PDAVIS video](https://drive.google.com/file/d/157mT8960m_QCm15i8HlB5SVyf45X_NUo/view?usp=sharing).\n  - [PDAVIS: Bio-inspired Polarization Event Camera](https://openaccess.thecvf.com/content/CVPR2023W/EventVision/html/Haessig_PDAVIS_Bio-Inspired_Polarization_Event_Camera_CVPRW_2023_paper.html). CVPR-W Proceedings (2023)\n- **Center Surround Event Camera (CSDVS)**: Delbruck, T., Li, C., Graca, R. \u0026 Mcreynolds, B.,  \n*[Utility and Feasibility of a Center Surround Event Camera](http://arxiv.org/abs/2202.13076)*  \narXiv [cs.CV] (2022) [CSDVS videos](https://sites.google.com/view/csdvs/home)\n  - Proposed architecture.\n\n\u003ca name=\"companies_sftwr\"\u003e\u003c/a\u003e\n# Companies working on Event-based Vision\n- [iniVation AG](https://inivation.com/) invents, produces and sells neuromorphic vision sensors (DAVIS, DVExplorer, and others), with a focus on event-based vision for business; supplies the advanced [DV event camera software](https://docs.inivation.com/software/introduction.html).\n- [iniLabs AG](https://inilabs.com/) invents neuromorphic technologies for *research*.\n- [Samsung](http://www.samsung.com) develops Gen2 and Gen3 dynamic vision sensors and event-based vision solutions.\n    - [IBM Research](http://www.research.ibm.com/articles/brain-chip.shtml) ([Synapse project](http://www.research.ibm.com/cognitive-computing/brainpower/)) and Samsung partenered to combine the [TrueNorth chip (brain) with a DVS (eye)](https://www.cnet.com/news/samsung-turns-ibms-brain-like-chip-into-a-digital-eye/).\n- [Prophesee](http://www.prophesee.ai) (Formerly [Chronocam](http://www.chronocam.com/)) is the inventor and supplier of 4 Event-Based sensors generations, including commercial-grade versions as well as industry’s largest software suite. The company focuses on Industrial, Mobile-IoT and Automotive applications.\n- [Insightness AG](http://www.insightness.com/) built visual systems to give mobile devices spatial awareness. [The Silicon Eye](http://www.insightness.com/?p=361) Technology. Aquired by Sony in 2019 and part of Sony Advanced Imager Sensors division.\n- [SLAMcore](https://www.slamcore.com/) develops Localisation and mapping solutions for AR/VR, robotics \u0026 autonomous vehicles.\n- [CelePixel](https://www.celepixel.com) (formerly Hillhouse Technology) offer integrated sensory platforms that incorporate various components and technologies, including a processing chipset and an image sensor (a dynamic vision sensor called CeleX).\n- [AIT Austrian Institute of Technology](https://www.ait.ac.at/en/research-fields/new-sensor-technologies/optical-sensor-systems-for-industrial-processes/) sells neuromorphic sensor products.\n    - [Inspection during production of carton packs](https://www.youtube.com/watch?v=8PZmb2z2bXw\u0026index=39\u0026list=PL659671AC92E70F19)\n    - [UCOS Universal Counting Sensor](https://www.ait.ac.at/fileadmin/mc/digital_safety_security/downloads/Factsheet_-_People-Counting-Sensor_en.pdf)\n    - [IVS Industrial Vision Sensor](https://www.ait.ac.at/fileadmin/mc/digital_safety_security/downloads/Factsheet_-_Industrial-Vision-Sensor_en.pdf)\n\n\u003ca name=\"neuromorphic-systems\"\u003e\u003c/a\u003e\n# Neuromorphic Systems\n- \u003ca name=\"SerranoGotarredona99tcas\"\u003e\u003c/a\u003e Serrano-Gotarredona, T. , Andreou, A.G. , Linares-Barranco, B.,  \n*[AER Image Filtering Architecture for Vision Processing Systems](https://doi.org/10.1109/81.788808)*,  \nIEEE Trans. Circuits Syst. I, Fundam. Theory Appl., 46(9):1064-1071, 1999.\n- \u003ca name=\"SerranoGotarredona06anips\"\u003e\u003c/a\u003e Serrano-Gotarredona, R., Oster, M., Lichtsteiner, P., Linares-Barranco, A., Paz-Vicente, R., Gomez-Rodriguez, F., Riis, H.K., Delbruck, T., Liu, S.-H., Zahnd, S., Whatley, A.M., Douglas, R., Hafliger, P., Jimenez-Moreno, G., Civit, A.,  Serrano-Gotarredona, T., Acosta-Jimenez, A., Linares-Barranco, B.,  \n*[AER building blocks for multi-layer multi-chip neuromorphic vision systems](http://papers.nips.cc/paper/2889-aer-building-blocks-for-multi-layer-multi-chip-neuromorphic-vision-systems.pdf)*,  \nAdvances in neural information processing systems, 1217-1224, 2006.\n- \u003ca name=\"Liu10conb\"\u003e\u003c/a\u003eLiu, S.-C. and Delbruck, T.,  \n*[Neuromorphic sensory systems](https://doi.org/10.1016/j.conb.2010.03.007)*,  \nCurrent Opinion in Neurobiology, 20:3(288-295), 2010.\n- \u003ca name=\"ZamarrenoRamos13tbcas\"\u003e\u003c/a\u003e Zamarreño-Ramos, C., Linares-Barranco, A., Serrano-Gotarredona, T., Linares-Barranco, B.,  \n*[Multi-Casting Mesh AER: A Scalable Assembly Approach for Reconfigurable Neuromorphic Structured AER Systems. Application to ConvNets](https://doi.org/10.1109/TBCAS.2012.2195725)*,  \nIEEE Trans. Biomed. Circuits Syst., 7(1):82-102, 2013.\n- \u003ca name=\"Liu14book\"\u003e\u003c/a\u003eLiu, S.-C., Delbruck, T., Indiveri, G., Whatley, A., Douglas, R.,  \n*[Event-Based Neuromorphic Systems](http://eu.wiley.com/WileyCDA/WileyTitle/productCd-1118927621.html)*,  \nWiley. ISBN: 978-1-118-92762-5, 2014.\n- \u003ca name=\"Chicca14ieee\"\u003e\u003c/a\u003eChicca, E., Stefanini, F., Bartolozzi, C., Indiveri, G.,  \n*[Neuromorphic Electronic Circuits for Building Autonomous Cognitive Systems](http://dx.doi.org/10.1109/JPROC.2014.2313954)*,  \nProc. IEEE, 102(9):1367-1388, 2014.\n- \u003ca name=\"Vanarse16fnins\"\u003e\u003c/a\u003eVanarse, A., Osseiran, A., Rassau, A,  \n*[A Review of Current Neuromorphic Approaches for Vision, Auditory, and Olfactory Sensors](http://dx.doi.org/10.3389/fnins.2016.00115)*,  \nFront. Neurosci. (2016), 10:115.\n- [Liu et al., Signal Process. Mag. 2019](#Liu19msp),  \n*Event-Driven Sensing for Efficient Perception: Vision and audition algorithms*.\n- [Event Cameras Tutorial - Tobi Delbruck, version 4.1](https://youtu.be/D6rv6q9XyWU), Sep. 18, 2020.\n- \u003ca name=\"Kirkland20spie\"\u003e\u003c/a\u003eKirkland, P., Di Caterina, G., Soraghan, J., Matich, G.,  \n[Neuromorphic technologies for defence and security](https://doi.org/10.1117/12.2575978),  \nSPIE vol 11540, Emerging Imaging and Sensing Technologies for Security and Defence V; and Advanced Manufacturing Technologies for Micro- and Nanosystems in Security and Defence III; 2020.\n\n\n\u003ca name=\"reviewpapers\"\u003e\u003c/a\u003e\n# Review / Overview papers\n\n\u003ca name=\"reviewpapers-bio\"\u003e\u003c/a\u003e\n## Sensor designs, Bio-inspiration\n- \u003ca name=\"Delbruck10iscas\"\u003e\u003c/a\u003eDelbruck, T.,  \n*[Activity-driven, event-based vision sensors](https://doi.org/10.1109/ISCAS.2010.5537149)*,  \nIEEE Int. Symp. Circuits and Systems (ISCAS), 2010. [PDF](https://e-lab.github.io/data/papers/ISCAS2010actsens.pdf).\n- \u003ca name=\"Posch12jinst\"\u003e\u003c/a\u003ePosch, C.,  \n*[Bio-inspired vision](https://doi.org/10.1088/1748-0221/7/01/C01054)*,  \nJ. of Instrumentation, 7 C01054, 2012.  Bio-inspired explanation of the DVS and the ATIS.  \n- Posch, C., Serrano-Gotarredona, T., Linares-Barranco, B., Delbruck, T.,  \n*[Retinomorphic Event-Based Vision Sensors: Bioinspired Cameras With Spiking Output](https://doi.org/10.1109/JPROC.2014.2346153),*  \nProc. IEEE (2014), 102(10):1470-1484. \n- \u003ca name=\"Posch15bicv\"\u003e\u003c/a\u003ePosch, C.,  \n*[Bioinspired vision sensing](https://doi.org/10.1002/9783527680863.ch2)*,  \nBiologically Inspired Computer Vision, Wiley-Blackwell, pp. 11-28, 2015. [book index](http://bicv.github.io/toc/index.html)\n- \u003ca name=\"Posch15ieee\"\u003e\u003c/a\u003ePosch, C., Benosman, R., Etienne-Cummings, R.,  \n*[How Neuromorphic Image Sensors Steal Tricks From the Human Eye](https://spectrum.ieee.org/biomedical/devices/how-neuromorphic-image-sensors-steal-tricks-from-the-human-eye)*, also published as *[Giving Machines Humanlike Eyes](https://doi.org/10.1109/MSPEC.2015.7335800)*,  \nIEEE Spectrum, 52(12):44-49, 2015.  \n- \u003ca name=\"Cho15sam\"\u003e\u003c/a\u003eCho, D., Lee, T.-J.,  \n*[A Review of Bioinspired Vision Sensors and Their Applications](https://doi.org/10.18494/SAM.2015.1133)*,  \nSensors and Materials, 27(6):447-463, 2015. [PDF](https://myukk.org/SM2017/sm_pdf/SM1083.pdf)\n- \u003ca name=\"Sandamirskaya22scirob\"\u003e\u003c/a\u003eSandamirskaya, Y., Kaboli, M., Conradt, J., Celikel, T.,  \n*[Neuromorphic computing hardware and neural architectures for robotics](https://doi.org/10.1126/scirobotics.abl8419)*,  \nScience Robotics, 7(67):eabl8419, 2022.\n\n\u003ca name=\"reviewpapers-algs\"\u003e\u003c/a\u003e\n## Algorithms, Applications\n- \u003ca name=\"Delbruck12eccvw\"\u003e\u003c/a\u003eDelbruck, T.,  \n*[Fun with asynchronous vision sensors and processing](https://www.ini.uzh.ch/~tobi/wiki/lib/exe/fetch.php?media=delbruck_funwithasynsensors_2012.pdf)*.  \nComputer Vision - ECCV 2012. Workshops and Demonstrations. Springer Berlin/Heidelberg, 2012. A position paper and summary of recent accomplishments of the INI Sensors' group.\n- \u003ca name=\"Delbruck16essderc\"\u003e\u003c/a\u003eDelbruck, T.,  \n*[Neuromorophic Vision Sensing and Processing (Invited paper)](https://doi.org/10.1109/ESSDERC.2016.7599576)*,  \n46th Eur. Solid-State Device Research Conference (ESSDERC), Lausanne, 2016, pp. 7-14.\n- Lakshmi, A., Chakraborty, A., Thakur, C.S.,  \n*[Neuromorphic vision: From sensors to event-based algorithms](https://doi.org/10.1002/widm.1310)*,  \nWiley Interdiscip. Rev. Data Min. Knowl. Discov. 9(4), 2019.\n- [Steffen, L. et al., Front. Neurorobot. 2019](#Steffen19fnbot),  \n*Neuromorphic Stereo Vision: A Survey of Bio-Inspired Sensors and Algorithms*.\n- [Gallego et al., TPAMI 2020](#Gallego20tpami),  \n*[Event-based Vision: A Survey](http://rpg.ifi.uzh.ch/docs/EventVisionSurvey.pdf)*.\n- \u003ca name=\"Chen20msp\"\u003e\u003c/a\u003eChen, G., Cao, H., Conradt, J., Tang, H., Rohrbein, F., Knoll, A.,  \n[Event-Based Neuromorphic Vision for Autonomous Driving: A Paradigm Shift for Bio-Inspired Visual Sensing and Perception](https://doi.org/10.1109/MSP.2020.2985815),  \nIEEE Signal Processing Magazine, 37(4):34-49, 2020.\n- \u003ca name=\"Chen20tits\"\u003e\u003c/a\u003eChen, G., Wang, F., Li, W., Hong, L., Conradt, J., Chen, J., Zhang, Z., Lu, Y., Knoll, A.,  \n*[NeuroIV: Neuromorphic Vision Meets Intelligent Vehicle Towards Safe Driving With a New Database and Baseline Evaluations](https://doi.org/10.1109/TITS.2020.3022921)*,  \nIEEE Trans. Intelligent Transportation Systems (TITS), 2020.\n- \u003ca name=\"Tayarani21fncir\"\u003e\u003c/a\u003eTayarani-Najaran, M.-H., Schmuker, M.,  \n*[Event-Based Sensing and Signal Processing in the Visual, Auditory, and Olfactory Domain: A Review](https://doi.org/10.3389/fncir.2021.610446)*,  \nFront. Neural Circuits 15:610446, 2021.\n- \u003ca name=\"Sun21hindawi\"\u003e\u003c/a\u003eSun, R. Shi, D., Zhang, Y., Li, R., Li, R.,  \n*[Data-Driven Technology in Event-Based Vision](https://doi.org/10.1155/2021/6689337)*,  \nComplexity, vol. 2021, Article ID 6689337.\n- \u003ca name=\"Bartolozzi22natcomm\"\u003e\u003c/a\u003eBartolozzi, C., Indiveri, G., Donati, E.,  \n*[Embodied neuromorphic intelligence](https://doi.org/10.1038/s41467-022-28487-2)*,  \nNat. Commun. 13:1024, 2022.\n- \u003ca name=\"Zou22mir\"\u003e\u003c/a\u003eZou, XL., Huang, T.J., Wu, S.,  \n*[Towards a New Paradigm for Brain-inspired Computer Vision](https://doi.org/10.1007/s11633-022-1370-z)*,  \nMach. Intell. Res., 19:412-424, 2022.\n- \u003ca name=\"Gehrig22arxiv\"\u003e\u003c/a\u003eGehrig, D., Scaramuzza, D.,  \n*[Are High-Resolution Cameras Really Needed?](https://arxiv.org/abs/2203.14672)*,  \narXiv, 2022. [YouTube](https://youtu.be/HV9_FhS-f88), [Code](https://uzh-rpg.github.io/eres/).  \n- \u003ca name=\"Ercan23cvprw\"\u003e\u003c/a\u003eErcan, B., Eker, O., Erdem, A., Erdem, E.,  \n*[EVREAL: Towards a Comprehensive Benchmark and Analysis Suite for Event-based Video Reconstruction](https://openaccess.thecvf.com/content/CVPR2023W/EventVision/papers/Ercan_EVREAL_Towards_a_Comprehensive_Benchmark_and_Analysis_Suite_for_Event-Based_CVPRW_2023_paper.pdf)*,  \nIEEE Conf. Computer Vision and Pattern Recognition Workshops (CVPRW), 2023. [PDF](https://openaccess.thecvf.com/content/CVPR2023W/EventVision/papers/Ercan_EVREAL_Towards_a_Comprehensive_Benchmark_and_Analysis_Suite_for_Event-Based_CVPRW_2023_paper.pdf), [Project Page](https://ercanburak.github.io/evreal.html), [Suppl.](https://openaccess.thecvf.com/content/CVPR2023W/EventVision/supplemental/Ercan_EVREAL_Towards_a_CVPRW_2023_supplemental.zip), [Code](https://github.com/ercanburak/EVREAL).\n- \u003ca name=\"Tapia23iros\"\u003e\u003c/a\u003eTapia, R., Rodríguez-Gómez, J.P., Sanchez-Diaz, J.A., Gañán, F.J., Rodríguez, I.G., Luna-Santamaria, J., Martínez-De Dios, J.R., Ollero, A.,  \n*[A Comparison Between Framed-Based and Event-Based Cameras for Flapping-Wing Robot Perception](https://doi.org/10.1109/IROS55552.2023.10342500)*,  \nIEEE/RSJ Int. Conf. Intelligent Robots and Systems (IROS), 2023, pp. 3025-3032. [PDF](https://arxiv.org/pdf/2309.05450), [YouTube](https://www.youtube.com/watch?v=a0X2NGPtY8w).  \n- \u003ca name=\"Ghosh24stereo\"\u003e\u003c/a\u003eGhosh, S., Gallego, G.,  \n*[Event-based Stereo Depth Estimation: A Survey](https://arxiv.org/abs/2409.17680)*,  \narXiv 2024,\n- \u003ca name=\"Cazzato2024application\"\u003e\u003c/a\u003eCazzato, D., Bono, F.,  \n*[An Application-Driven Survey on Event-Based Neuromorphic Computer Vision](https://www.mdpi.com/2078-2489/15/8/472)*,  \nInformation 15.8 (2024): 472.\n- \u003ca name=\"AliAkbarpour2024Emerging\"\u003e\u003c/a\u003eAliAkbarpour, H., Moori, A., Khorramdel, J., Blasch, E., Tahri, O.,  \n*[Emerging Trends and Applications of Neuromorphic Dynamic Vision Sensors: A Survey](https://doi.org/10.1109/SR.2024.3513952)*,  \nIEEE Sensors Reviews (2024), vol 1, pp. 14-63. [PDF](https://ieeexplore.ieee.org/iel8/10347229/10787061/10795229.pdf)\n- \u003ca name=\"Iddrisu25access\"\u003e\u003c/a\u003eIddrisu, K., Shariff, W., Corcoran, P., O’Connor, N., Lemley, J., Little, S.,  \n*[Event Camera Based Eye Motion Analysis: A Survey](https://doi.org/10.1109/ACCESS.2024.3462109)*,  \nIEEE Access, 12:136783-136804 (2025).\n\n\u003ca name=\"algorithms\"\u003e\u003c/a\u003e\n# Algorithms\n\n\u003ca name=\"feature-detection\"\u003e\u003c/a\u003e\n## Feature Detection and Tracking\n- \u003ca name=\"Litzenberger06dspws\"\u003e\u003c/a\u003eLitzenberger, M., Posch, C., Bauer, D., Belbachir, A. N., Schon. P., Kohn, B., Garn, H.,  \n*[Embedded Vision System for Real-Time Object Tracking using an Asynchronous Transient Vision Sensor](https://doi.org/10.1109/DSPWS.2006.265448)*,  \nIEEE 12th Digital Signal Proc. Workshop and 4th IEEE Signal Proc. Education Workshop, Teton National Park, WY, 2006, pp. 173-178. [PDF](http://www.belbachir.info/PDF/dsp2006.pdf)\n    - \u003ca name=\"Litzenberger06itsc\"\u003e\u003c/a\u003eLitzenberger, M., Kohn, B., Belbachir, A.N., Donath, N., Gritsch, G., Garn, H., Posch, C., Schraml, S.,  \n*[Estimation of Vehicle Speed Based on Asynchronous Data from a Silicon Retina Optical Sensor](https://doi.org/10.1109/ITSC.2006.1706816)*,  \nIEEE Intelligent Transportation Systems Conf. (ITSC), 2006, pp. 653-658. [PDF](http://belbachir.info/PDF/itsc2006.pdf)\n    - \u003ca name=\"Bauer07ejes\"\u003e\u003c/a\u003eBauer, D., Belbachir, A. N., Donath, N., Gritsch, G., Kohn, B., Litzenberger, M., Posch, C., Schön, P., Schraml, S.,  \n*[Embedded Vehicle Speed Estimation System Using an Asynchronous Temporal Contrast Vision Sensor](https://link.springer.com/article/10.1155/2007/82174)*,  \nEURASIP J. Embedded Systems, 2007:082174. [PDF](http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.385.424\u0026rep=rep1\u0026type=pdf)\n    - \u003ca name=\"Litzenberger07icdsc\"\u003e\u003c/a\u003eLitzenberger, M., Belbachir, N., Schon, P., Posch, C.,  \n*[Embedded Smart Camera for High Speed Vision](https://doi.org/10.1109/ICDSC.2007.4357509)*,  \nACM/IEEE Int. Conf. on Distributed Smart Cameras, 2007. [PDF](http://belbachir.info/PDF/icdsc2007.pdf)\n- \u003ca name=\"Ni12tro\"\u003e\u003c/a\u003eNi, Z., Bolopion, A., Agnus, J., Benosman, R., Regnier, S.,  \n*[Asynchronous event-based visual shape tracking for stable haptic feedback in microrobotics](https://doi.org/10.1109/TRO.2012.2198930)*,  \nIEEE Trans. Robot. (TRO), 28(5):1081-1089, 2012.  \n    - [Ni, Ph.D. Thesis, 2013](#Ni13PhD),  \n*Asynchronous Event Based Vision:  Algorithms and Applications to Microrobotics*.\n    - \u003ca name=\"Ni15neco\"\u003e\u003c/a\u003eNi, Z., Ieng, S. H., Posch, C., Regnier, S., Benosman, R.,  \n*[Visual Tracking Using Neuromorphic Asynchronous Event-Based Cameras](https://doi.org/10.1162/NECO_a_00720)*,  \nNeural Computation (2015), 27(4):925-953. [YouTube](https://youtu.be/eQ7reEN9PrA)\n- \u003ca name=\"Piatkowska12cvprw\"\u003e\u003c/a\u003ePiatkowska, E., Belbachir, A. N., Schraml, S., Gelautz, M.,  \n*[Spatiotemporal multiple persons tracking using Dynamic Vision Sensor](https://doi.org/10.1109/CVPRW.2012.6238892)*,  \nIEEE Conf. Computer Vision and Pattern Recognition Workshops (CVPRW), 2012, pp. 35-40. [PDF](https://publik.tuwien.ac.at/files/PubDat_209369.pdf)\n- \u003ca name=\"Lagorce15fnins\"\u003e\u003c/a\u003eLagorce, X., Ieng, S.-H., Clady, X., Pfeiffer, M., Benosman, R.,  \n*[Spatiotemporal features for asynchronous event-based data](http://dx.doi.org/10.3389/fnins.2015.00046)*,  \nFront. Neurosci. (2015), 9:46.\n    - \u003ca name=\"Lagorce13iros\"\u003e\u003c/a\u003eLagorce, X., Ieng, S. H., Benosman, R.,  \n*[Event-based features for robotic vision](http://dx.doi.org/10.1109/IROS.2013.6696960)*,  \nIEEE/RSJ Int. Conf. Intelligent Robots and Systems (IROS), 2013, pp. 4214-4219.\n- \u003ca name=\"Saner14vmv\"\u003e\u003c/a\u003eSaner, D., Wang, O., Heinzle, S., Pritch, Y., Smolic, A., Sorkine-Hornung, A., Gross, M.,  \n*[High-Speed Object Tracking Using an Asynchronous Temporal Contrast Sensor](http://dx.doi.org/10.2312/vmv.20141280)*,  \nInt. Symp. Vision, Modeling and Visualization (VMV), 2014. [PDF](http://ahornung.net/files/pub/2014-vmv-siliconretina-saner.pdf)\n- \u003ca name=\"Lagorce15tnnls\"\u003e\u003c/a\u003eLagorce, X., Meyer, C., Ieng, S. H., Filliat, D., Benosman, R.,  \n*[Asynchronous Event-Based Multikernel Algorithm for High-Speed Visual Features Tracking](https://doi.org/10.1109/TNNLS.2014.2352401)*,  \nIEEE Trans. Neural Netw. Learn. Syst. (TNNLS), 26(8):1710-1720, 2015. [YouTube](https://youtu.be/ze8Wgou9yA4)\n    - \u003ca name=\"Lagorce14biocas\"\u003e\u003c/a\u003eLagorce, X., Meyer, C., Ieng, S. H., Filliat, D., Benosman, R.,  \n*[Live demonstration: Neuromorphic event-based multi-kernel algorithm for high speed visual features tracking](https://doi.org/10.1109/BioCAS.2014.6981681)*,  \nIEEE Biomedical Circuits and Systems Conference (BioCAS), 2014, pp. 178.\n- \u003ca name=\"Reverter15tnnls\"\u003e\u003c/a\u003eReverter Valeiras, D., Lagorce, X., Clady, X., Bartolozzi, C., Ieng, S., Benosman, R.,  \n*[An Asynchronous Neuromorphic Event-Driven Visual Part-Based Shape Tracking](https://doi.org/10.1109/TNNLS.2015.2401834)*,  \nIEEE Trans. Neural Netw. Learn. Syst. (TNNLS), 26(12):3045-3059, 2015. [YouTube](https://youtu.be/XeQYNYESJtQ)\n- \u003ca name=\"LinaresBarranco15iscas\"\u003e\u003c/a\u003eLinares-Barranco, A., Gómez-Rodríguez, F., Villanueva, V., Longinotti, L., Delbrück, T.,    \n*[A USB3.0 FPGA event-based filtering and tracking framework for dynamic vision sensors](https://doi.org/10.1109/ISCAS.2015.7169172)*,  \nIEEE Int. Symp. Circuits and Systems (ISCAS), 2015.\n- \u003ca name=\"LinaresBarranco15iscas\"\u003e\u003c/a\u003eLeow, H. S., Nikolic, K.,  \n*[Machine vision using combined frame-based and event-based vision sensor](https://doi.org/10.1109/ISCAS.2015.7168731)*,  \nIEEE Int. Symp. Circuits and Systems (ISCAS), 2015.\n- \u003ca name=\"Liu16iscas\"\u003e\u003c/a\u003eLiu, H., Moeys, D. P., Das, G., Neil, D., Liu, S.-C., Delbruck, T.,  \n*[Combined frame- and event-based detection and tracking](https://doi.org/10.1109/ISCAS.2016.7539103)*,  \nIEEE Int. Symp. Circuits and Systems (ISCAS), 2016.\n- \u003ca name=\"Tedaldi16ebccsp\"\u003e\u003c/a\u003eTedaldi, D., Gallego, G., Mueggler, E., Scaramuzza, D.,  \n*[Feature detection and tracking with the dynamic and active-pixel vision sensor (DAVIS)](https://doi.org/10.1109/EBCCSP.2016.7605086)*,  \nIEEE Int. Conf. Event-Based Control Comm. and Signal Proc. (EBCCSP), 2016. [PDF](http://rpg.ifi.uzh.ch/docs/EBCCSP16_Tedaldi.pdf), [YouTube](https://www.youtube.com/watch?v=nglfEkiK308)\n    - [Kueng et al., IROS 2016](#Kueng16iros)\n*Low-Latency Visual Odometry using Event-based Feature Tracks*.\n- \u003ca name=\"Brandli16ebccsp\"\u003e\u003c/a\u003eBraendli, C., Strubel, J., Keller, S., Scaramuzza, D., Delbruck, T.,  \n*[ELiSeD - An Event-Based Line Segment Detector](https://doi.org/10.1109/EBCCSP.2016.7605244)*,  \nInt. Conf. on Event-Based Control Comm. and Signal Proc. (EBCCSP), 2016. [PDF](http://rpg.ifi.uzh.ch/docs/EBCCSP16_Braendli.pdf)\n- \u003ca name=\"Glover16iros\"\u003e\u003c/a\u003eGlover, A. and Bartolozzi, C.,  \n*[Event-driven ball detection and gaze fixation in clutter](https://doi.org/10.1109/IROS.2016.7759345)*,  \nIEEE/RSJ Int. Conf. Intelligent Robots and Systems (IROS), 2016, pp. 2203-2208. [YouTube](https://youtu.be/n6qTkw5U7YI), [Code](https://github.com/robotology/event-driven)\n    - \u003ca name=\"Glover17iros\"\u003e\u003c/a\u003eGlover, A. and Bartolozzi, C.,  \n*[Robust Visual Tracking with a Freely-moving Event Camera](https://doi.org/10.1109/IROS.2017.8206226)*,  \nIEEE/RSJ Int. Conf. Intelligent Robots and Systems (IROS), 2017. [YouTube](https://youtu.be/xS-7xYRYSLc), [Code](https://github.com/robotology/event-driven)\n    - \u003ca name=\"Glover18irosw\"\u003e\u003c/a\u003eGlover, A., Stokes, A.B., Furber, S., Bartolozzi, C.,  \n*[ATIS + SpiNNaker: a Fully Event-based Visual Tracking Demonstration](https://arxiv.org/pdf/1912.01320)*,  \nIEEE/RSJ Int. Conf. Intelligent Robots and Systems Workshops (IROSW), 2018. Workshop on Unconventional Sensing and Processing for Robotic Visual Perception.\n- \u003ca name=\"Clady17fnins\"\u003e\u003c/a\u003eClady, X., Maro, J.-M., Barré, S., Benosman, R. B.,  \n*[A Motion-Based Feature for Event-Based Pattern Recognition](https://doi.org/10.3389/fnins.2016.00594)*.  \nFront. Neurosci. (2017), 10:594. \n- \u003ca name=\"Zhu17icra\"\u003e\u003c/a\u003eZhu, A., Atanasov, N., Daniilidis, K.,  \n*[Event-based Feature Tracking with Probabilistic Data Association](https://doi.org/10.1109/ICRA.2017.7989517)*,  \nIEEE Int. Conf. Robotics and Automation (ICRA), 2017. [PDF](https://fling.seas.upenn.edu/~alexzhu/dynamic/wp-content/uploads/2017/07/EventBasedFeatureTrackingICRA2017.pdf), [YouTube](https://youtu.be/m93XCqAS6Fc), [Code](https://github.com/daniilidis-group/event_feature_tracking)\n- \u003ca name=\"BarriosAviles18electronics\"\u003e\u003c/a\u003eBarrios-Avilés, J., Iakymchuk, T., Samaniego, J., Medus, L.D., Rosado-Muñoz, A.,  \n*[Movement Detection with Event-Based Cameras: Comparison with Frame-Based Cameras in Robot Object Tracking Using Powerlink Communication](https://doi.org/10.3390/electronics7110304)*,  \nElectronics 2018, 7, 304. [PDF pre-print](https://arxiv.org/abs/1707.07188)\n- \u003ca name=\"Li17bmvc\"\u003e\u003c/a\u003eLi, J., Shi, F., Liu, W., Zou, D., Wang, Q., Park, P.K.J., Ryu, H.,  \n*[Adaptive Temporal Pooling for Object Detection using Dynamic Vision Sensor](https://www.dropbox.com/s/m77i7cqqy7xbg51/0099.pdf?dl=1)*,  \nBritish Machine Vision Conf. (BMVC), 2017.\n- \u003ca name=\"Peng17tnnls\"\u003e\u003c/a\u003ePeng, X., Zhao, B., Yan, R., Tang H., Yi, Z.,  \n*[Bag of Events: An Efficient Probability-Based Feature Extraction Method for AER Image Sensors](http://dx.doi.org/10.1109/TNNLS.2016.2536741)*,  \nIEEE Trans. Neural Netw. Learn. Syst. (TNNLS), 28(4):791-803, 2017.\n- \u003ca name=\"Ramesh19tpami\"\u003e\u003c/a\u003eRamesh, B., Yang, H., Orchard, G., Le Thi, N.A., Xiang, C,  \n*[DART: Distribution Aware Retinal Transform for Event-based Cameras](https://doi.org/10.1109/TPAMI.2019.2919301)*,  \nIEEE Trans. Pattern Anal. Machine Intell. (TPAMI), 2019. [PDF](https://arxiv.org/pdf/1710.10800.pdf)\n- \u003ca name=\"Gehrig19ijcv\"\u003e\u003c/a\u003eGehrig, D., Rebecq, H., Gallego, G., Scaramuzza, D.,  \n*[EKLT: Asynchronous, Photometric Feature Tracking using Events and Frames](http://rpg.ifi.uzh.ch/docs/IJCV19_Gehrig.pdf)*,  \nInt. J. Computer Vision (IJCV), 2019. [YouTube](https://youtu.be/ZyD1YPW1h4U), [Tracking code](https://github.com/uzh-rpg/rpg_eklt), [Evaluation code](https://github.com/uzh-rpg/rpg_feature_tracking_analysis)\n    - \u003ca name=\"Gehrig18eccv\"\u003e\u003c/a\u003eGehrig, D., Rebecq, H., Gallego, G., Scaramuzza, D.,  \n*[Asynchronous, Photometric Feature Tracking using Events and Frames](http://rpg.ifi.uzh.ch/docs/ECCV18_Gehrig.pdf)*,  \nEuropean Conf. Computer Vision (ECCV), 2018. [Poster](http://rpg.ifi.uzh.ch/docs/ECCV18_Gehrig_poster.pdf), [YouTube](https://youtu.be/A7UfeUnG6c4), [Oral presentation](https://youtu.be/7EvY8SxdLl8), [Tracking code](https://github.com/uzh-rpg/rpg_eklt), [Evaluation code](https://github.com/uzh-rpg/rpg_feature_tracking_analysis)\n- \u003ca name=\"Everding18fnbot\"\u003e\u003c/a\u003eEverding, L., Conradt, J.,  \n*[Low-Latency Line Tracking Using Event-Based Dynamic Vision Sensors](https://doi.org/10.3389/fnbot.2018.00004)*,  \nFront. Neurorobot. 12:4, 2018.  [Videos](http://www.frontiersin.org/articles/10.3389/fnbot.2018.00004/full#supplementary-material)\n- \u003ca name=\"LinaresBarrancoA18entropy\"\u003e\u003c/a\u003eLinares-Barranco, A., Liu, H., Rios-Navarro, A., Gomez-Rodriguez, F., Moeys, D., Delbruck, T.  \n*[Approaching Retinal Ganglion Cell Modeling and FPGA Implementation for Robotics](https://doi.org/10.3390/e20060475)*,  \nEntropy 2018, 20(6), 475.  \n- \u003ca name=\"Mitrokhin18iros\"\u003e\u003c/a\u003eMitrokhin, A., Fermüller, C., Parameshwara, C., Aloimonos, Y.,  \n*[Event-based Moving Object Detection and Tracking](https://doi.org/10.1109/IROS.2018.8593805)*,  \nIEEE/RSJ Int. Conf. Intelligent Robots and Systems (IROS), 2018. [PDF](https://arxiv.org/pdf/1803.04523.pdf), [YouTube](https://youtu.be/UCAJi0ZFaZ8), [Project page and Dataset](http://prg.cs.umd.edu/BetterFlow.html)\n- \u003ca name=\"Iacono18iros\"\u003e\u003c/a\u003eIacono, M., Weber, S., Glover, A., Bartolozzi, C.,  \n*[Towards Event-Driven Object Detection with Off-The-Shelf Deep Learning](https://doi.org/10.1109/IROS.2018.8594119)*,  \nIEEE/RSJ Int. Conf. Intelligent Robots and Systems (IROS), 2018.\n- \u003ca name=\"Ramesh18bmvc\"\u003e\u003c/a\u003eRamesh, B., Zhang, S., Lee, Z.-W., Gao, Z., Orchard, G., Xiang, C.,  \n*[Long-term object tracking with a moving event camera](http://bmvc2018.org/contents/papers/0814.pdf)*,  \nBritish Machine Vision Conf. (BMVC), 2018.  [Video](http://bmvc2018.org/contents/supplementary/video/0814_video.mp4)\n    - \u003ca name=\"Ramesh20arxiv\"\u003e\u003c/a\u003eRamesh, B., Zhang, S., Yang, H., Ussa, A., Ong, M., Orchard, G., Xiang, C.,  \n*[e-TLD: Event-based Framework for Dynamic Object Tracking](https://arxiv.org/pdf/2009.00855.pdf)*,  \narXiv, 2020.\n- \u003ca name=\"Dardelet18arxiv\"\u003e\u003c/a\u003eDardelet, L., Ieng, S.-H., Benosman, R.,  \n*[Event-Based Features Selection and Tracking from Intertwined Estimation of Velocity and Generative Contours](https://arxiv.org/pdf/1811.07839)*,  \narXiv:1811.07839, 2018.\n- \u003ca name=\"Wu18chreoc\"\u003e\u003c/a\u003eWu, J., Zhang, K., Zhang, Y., Xie, X., Shi, G.,  \n*[High-Speed Object Tracking with Dynamic Vision Sensor](https://doi.org/10.1007/978-981-13-6553-9_18)*,  \nChina High Resolution Earth Observation Conference (CHREOC), 2018.\n- \u003ca name=\"Huang18tcsvt\"\u003e\u003c/a\u003eHuang, J., Wang, S., Guo, M., Chen, S.,  \n*[Event-Guided Structured Output Tracking of Fast-Moving Objects Using a CeleX Sensor](https://doi.org/10.1109/TCSVT.2018.2841516)*,  \nIEEE Trans. Circuits Syst. Video Technol. (TCSVT), 28(9):2413-2417, 2018.\n- \u003ca name=\"Renner19cvprw\"\u003e\u003c/a\u003eRenner, A., Evanusa, M., Sandamirskaya, Y.,  \n*[Event-based attention and tracking on neuromorphic hardware](http://openaccess.thecvf.com/content_CVPRW_2019/papers/EventVision/Renner_Event-Based_Attention_and_Tracking_on_Neuromorphic_Hardware_CVPRW_2019_paper.pdf)*,  \nIEEE Conf. Computer Vision and Pattern Recognition Workshops (CVPRW), 2019. [Video pitch](https://youtu.be/eWBEJOr056E)\n- \u003ca name=\"Foster19elim\"\u003e\u003c/a\u003eFoster, B.J., Ye, D.H., Bouman, C.A.,  \n*[Multi-target tracking with an event-based vision sensor and a partial-update GMPHD filter](https://www.ingentaconnect.com/contentone/ist/ei/2019/00002019/00000013/art00002?crawler=true\u0026mimetype=application/pdf)*,  \nIS\u0026T International Symposium on Electronic Imaging 2019. Computational Imaging XVII.\n- \u003ca name=\"Alzugaray193dv\"\u003e\u003c/a\u003eAlzugaray, I., Chli, M.,  \n*[Asynchronous Multi-Hypothesis Tracking of Features with Event Cameras](https://doi.org/10.3929/ethz-b-000360434)*,  \nIEEE Int. Conf. 3D Vision (3DV), 2019. [PDF](https://doi.org/10.3929/ethz-b-000360434), [Code](https://github.com/ialzugaray/haste), [YouTube](https://youtu.be/eguV_AIbteU)\n- \u003ca name=\"LinaresBarranco19access\"\u003e\u003c/a\u003eLinares-Barranco, A., Perez-Pena, F., Moeys, D.P., Gomez-Rodriguez, F., Jimenez-Moreno, G., Delbruck, T.  \n*[Low Latency Event-based Filtering and Feature Extraction for Dynamic Vision Sensors in Real-Time FPGA Applications](https://doi.org/10.1109/ACCESS.2019.2941282)*,  \nIEEE Access, 7:134926-134942, 2019. [Code](https://github.com/RTC-research-group/EDIP_library)\n- \u003ca name=\"Li19access\"\u003e\u003c/a\u003eLi, K., Shi, D., Zhang, Y., Li, R., Qin, W., Li, R.,  \n*[Feature Tracking Based on Line Segments With the Dynamic and Active-Pixel Vision Sensor (DAVIS)](https://doi.org/10.1109/ACCESS.2019.2933594)*,  \nIEEE Access, 7:110874-110883, 2019.\n- \u003ca name=\"Bolten19iccs\"\u003e\u003c/a\u003eBolten T., Pohle-Fröhlich R., Tönnies K.D.,  \n*[Application of Hierarchical Clustering for Object Tracking with a Dynamic Vision Sensor](https://doi.org/10.1007/978-3-030-22750-0_13)*,  \nInt. Conf. Computational Science (ICCS) 2019. [PDF](https://www.hs-niederrhein.de/fileadmin/dateien/Institute_und_Kompetenzzentren/iPattern/selfarchived/bolten-iccs-2019.pdf)\n- \u003ca name=\"Chen19mm\"\u003e\u003c/a\u003eChen, H., Wu, Q., Liang, Y., Gao, X., Wang, H.,  \n*[Asynchronous Tracking-by-Detection on Adaptive Time Surfaces for Event-based Object Tracking](https://doi.org/10.1145/3343031.3350975)*,  \nACM Int. Conf. on Multimedia (MM), 2019.\n- \u003ca name=\"Reverter19tnnls\"\u003e\u003c/a\u003eReverter Valeiras, D., Clady, X., Ieng, S.-H., Benosman, R.,  \n*[Event-Based Line Fitting and Segment Detection Using a Neuromorphic Visual Sensor](https://doi.org/10.1109/TNNLS.2018.2807983)*,  \nIEEE Trans. Neural Netw. Learn. Syst. (TNNLS), 30(4):1218-1230, 2019. \n- \u003ca name=\"Li19fnbot\"\u003e\u003c/a\u003eLi, H., Shi, L., \n*[Robust Event-Based Object Tracking Combining Correlation Filter and CNN Representation](https://doi.org/10.3389/fnbot.2019.00082)*,  \nFront. Neurorobot. 13:82, 2019. [Dataset](https://figshare.com/s/70565903453eef7c3965)\n- \u003ca name=\"Chen2020arxiv\"\u003e\u003c/a\u003eChen, H., Suter, D., Wu, Q., Wang, H.,  \n*[End-to-end Learning of Object Motion Estimation from Retinal Events for Event-based Object Tracking](https://doi.org/10.1609/aaai.v34i07.6625)*,  \nAAAI Conf. Artificial Intelligence, 2020. [PDF](https://www.aaai.org/Papers/AAAI/2020GB/AAAI-ChenH.2586.pdf), [PDF](https://arxiv.org/pdf/2002.05911).\n- \u003ca name=\"Monforte20aicas\"\u003e\u003c/a\u003eMonforte, M., Arriandiaga, A., Glover, A., Bartolozzi, C.,  \n*[Exploiting Event Cameras for Spatio-Temporal Prediction of Fast-Changing Trajectories](https://arxiv.org/pdf/2001.01248)*,  \nIEEE Int. Conf. Artificial Intelligence Circuits and Systems (AICAS), 2020.\n- \u003ca name=\"Sengupta20aicas\"\u003e\u003c/a\u003eSengupta, J. P., Kubendran, R., Neftci, E., Andreou, A. G.,  \n*[High-Speed, Real-Time, Spike-Based Object Tracking and Path Prediction on Google Edge TPU.](https://par.nsf.gov/servlets/purl/10212648)*  \nIEEE Int. Conf. Artificial Intelligence Circuits and Systems (AICAS), 2020, pp. 134-135.  \n- \u003ca name=\"Seok20wacv\"\u003e\u003c/a\u003eSeok, H., Lim, J.,  \n*[Robust Feature Tracking in DVS Event Stream using Bezier Mapping](http://openaccess.thecvf.com/content_WACV_2020/papers/Seok_Robust_Feature_Tracking_in_DVS_Event_Stream_using_Bezier_Mapping_WACV_2020_paper.pdf)*,  \nIEEE Winter Conf. Applications of Computer Vision (WACV), 2020.  [YouTube](https://youtu.be/mskBdueW9Hc)\n- \u003ca name=\"Xu20cvpr\"\u003e\u003c/a\u003eXu, L., Xu, W., Golyanik, V., Habermann, M., Fang, L., Theobalt, C.,  \n*[EventCap: Monocular 3D Capture of High-Speed Human Motions using an Event Camera](https://arxiv.org/pdf/1908.11505)*,  \nIEEE Conf. Computer Vision and Pattern Recognition (CVPR), 2020. [ZDNet news](https://www.zdnet.com/article/high-speed-motion-capture-using-a-single-event-camera/)\n- \u003ca name=\"RodriguezGomez20icra\"\u003e\u003c/a\u003eRodríguez-Gómez, J.P., Gómez Eguíluz, A., Martínez-de Dios, J.R., Ollero, A.,  \n*[Asynchronous event-based clustering and tracking for intrusion monitoring](https://ras.papercept.net/proceedings/ICRA20/1523.pdf)*,  \nIEEE Int. Conf. Robotics and Automation (ICRA), 2020. [PDF](https://zenodo.org/record/3816654#.XxHQ9hFS9hE).\n- [Boettiger, J. P., MSc 2020](#Boettiger20MSc),\n*A Comparative Evaluation of the Detection and Tracking Capability Between Novel Event-Based and Conventional Frame-Based Sensors*.\n- \u003ca name=\"Sarmadi20arxiv\"\u003e\u003c/a\u003eSarmadi, H., Muñoz-Salinas, R., Olivares-Mendez, M. A., Medina-Carnicer, R.,  \n*[Detection of Binary Square Fiducial Markers Using an Event Camera](https://arxiv.org/pdf/2012.06516)*,  \narXiv, 2020.\n- \u003ca name=\"Alzugaray20bmvc\"\u003e\u003c/a\u003eAlzugaray, I., Chli, M.,  \n*[HASTE: multi-Hypothesis Asynchronous Speeded-up Tracking of Events](https://www.bmvc2020-conference.com/conference/papers/paper_0744.html)*,  \nBritish Machine Vision Conf. (BMVC), 2020. [PDF](https://www.bmvc2020-conference.com/assets/papers/0744.pdf), [Suppl. Mat.](https://www.bmvc2020-conference.com/assets/supp/0744_supp.zip), [Code](https://github.com/ialzugaray/haste), [Presentation](https://www.bmvc2020-conference.com/conference/papers/paper_0744.html), [Youtube](https://youtu.be/6DZxIzrVLcI)\n- \u003ca name=\"Liu21arxiv\"\u003e\u003c/a\u003eLiu, Z., Fu, Y.,  \n*[e-ACJ: Accurate Junction Extraction For Event Cameras](https://arxiv.org/pdf/2101.11251)*,  \narXiv, 2021.\n- \u003ca name=\"Dong21icmva\"\u003e\u003c/a\u003eDong, Y., Zhang, T.,  \n*[Standard and Event Cameras Fusion for Feature Tracking](https://dl.acm.org/doi/10.1145/3459066.3459075)*,  \nInt. Conf. on Machine Vision and Applications (ICMVA), 2021. [Code](https://github.com/LarryDong/FusionTracking)\n- \u003ca name=\"Mondal21iccvw\"\u003e\u003c/a\u003eMondal, A., Shashant, R., Giraldo, J. H., Bouwmans, T., Chowdhury, A. S.,  \n*[Moving Object Detection for Event-based Vision using Graph Spectral Clustering](https://openaccess.thecvf.com/content/ICCV2021W/GSP-CV/papers/Mondal_Moving_Object_Detection_for_Event-Based_Vision_Using_Graph_Spectral_Clustering_ICCVW_2021_paper.pdf)*,  \nIEEE Int. Conf. Computer Vision Workshop (ICCVW), 2021. [Youtube](https://youtu.be/ST6Z-3SlNS4), [Code](https://github.com/anindya2001/GSCEventMOD).\n- \u003ca name=\"Wang21arxiv\"\u003e\u003c/a\u003eXiao Wang, Jianing Li, Lin Zhu, Zhipeng Zhang, Zhe Chen, Xin Li, Yaowei Wang, Yonghong Tian, Feng Wu,  \n*[VisEvent: Reliable Object Tracking via Collaboration of Frame and Event Flows](https://arxiv.org/abs/2108.05015)*,  \narXiv, 2021. [Code](https://github.com/wangxiao5791509/VisEvent_SOT_Benchmark)\n- [Alzugaray, I., Ph.D. Thesis, 2022](#Alzugaray22PhD),  \n*Event-driven Feature Detection and Tracking for Visual SLAM*.\n- \u003ca name=\"zhang2021multi\"\u003e\u003c/a\u003eZhang, J., Zhao, K., Dong, B., Fu, Y., Wang, Y., Yang, X., Yin, B.,  \n*[Multi-domain collaborative feature representation for robust visual object tracking](https://doi.org/10.1007/s00371-021-02237-9)*,  \nThe Visual Computer, 2021. [PDF](https://link.springer.com/article/10.1007/s00371-021-02237-9), [Project](https://zhangjiqing.com/publication/multi-domain-collaborative-feature-representation-for-robust-visual-object-tracking-the-visual-computer-2021-proc-cgi-2021-/).\n- \u003ca name=\"Zhang2021iccv\"\u003e\u003c/a\u003eZhang, J., Yang, X., Fu, Y., Wei, X., Yin, B., Dong, B.,  \n*[Object Tracking by Jointly Exploiting Frame and Event Domain](https://openaccess.thecvf.com/content/ICCV2021/papers/Zhang_Object_Tracking_by_Jointly_Exploiting_Frame_and_Event_Domain_ICCV_2021_paper.pdf)*,  \nIEEE Int. Conf. Computer Vision (ICCV), 2021. [Project](https://zhangjiqing.com/publication/iccv21_fe108_tracking/), [PDF](https://arxiv.org/abs/2109.09052), [Code](https://github.com/Jee-King/ICCV2021_Event_Frame_Tracking), [Dataset](https://zhangjiqing.com/dataset/).\n- \u003ca name=\"Dietsche21iros\"\u003e\u003c/a\u003eDietsche, A., Cioffi, G., Hidalgo-Carrio, J., Scaramuzza, D.,  \n*[Powerline Tracking with Event Cameras](http://dx.doi.org/10.1109/IROS51168.2021.9636824)*,  \nIEEE/RSJ Int. Conf. Intelligent Robots and Systems (IROS), 2021. [PDF](https://rpg.ifi.uzh.ch/docs/IROS21_Dietsche.pdf), [Dataset](https://download.ifi.uzh.ch/rpg/powerline_tracking_dataset/), [YouTube](https://www.youtube.com/watch?v=KnBJqed5qDI), [Code](https://github.com/uzh-rpg/line_tracking_with_event_cameras).\n- \u003ca name=\"Li21icra\"\u003e\u003c/a\u003eLi, H., Stueckler, J.,  \n*[Tracking 6-DoF Object Motion from Events and Frames](https://arxiv.org/pdf/2103.15568.pdf)*,  \nIEEE Int. Conf. Robotics and Automation (ICRA), 2021.\n- \u003ca name=\"Zhang2022cvpr\"\u003e\u003c/a\u003eZhang, J., Dong, B., Zhang, H., Ding, J., Heide, F., Yin, B., Yang, X.,  \n*[Spiking Transformers for Event-based Single Object Tracking](https://openaccess.thecvf.com/content/CVPR2022/papers/Zhang_Spiking_Transformers_for_Event-Based_Single_Object_Tracking_CVPR_2022_paper.pdf)*,  \nIEEE Conf. Computer Vision and Pattern Recognition (CVPR), 2022. [Project](https://zhangjiqing.com/publication/stnet/), [PDF](https://openaccess.thecvf.com/content/CVPR2022/papers/Zhang_Spiking_Transformers_for_Event-Based_Single_Object_Tracking_CVPR_2022_paper.pdf), [Code](https://github.com/Jee-King/CVPR2022_STNet).\n- [Gao, et at., FPGA, 2022](#Gao22FPGA),  \n*REMOT: A Hardware-Software Architecture for Attention-Guided Multi-Object Tracking with Dynamic Vision Sensors on FPGAs*.\n- \u003ca name=\"el2022high\"\u003e\u003c/a\u003eEl Shair, Z., Rawashdeh, S.A.,  \n*[High-Temporal-Resolution Object Detection and Tracking using Images and Events](https://doi.org/10.3390/jimaging8080210)*,  \nJournal of Imaging, 2022. [PDF](https://www.mdpi.com/2313-433X/8/8/210/pdf), [Dataset](http://sar-lab.net/event-based-vehicle-detection-and-tracking-dataset/).\n- \u003ca name=\"hu2022eCDT\"\u003e\u003c/a\u003e Hu, S., Kim, Y., Lim, H., Lee, A., Myung, H.,  \n[eCDT: Event Clustering for Simultaneous Feature Detection and Tracking](https://doi.org/10.1109/IROS47612.2022.9981451),  \nIEEE/RSJ Int. Conf. Intelligent Robots and Systems (IROS), 2022. [YouTube](https://www.youtube.com/watch?v=eS-3PP-8sek\u0026ab_channel=KAISTUrbanRoboticsLab)\n- \u003ca name=\"zhu2022learning\"\u003e\u003c/a\u003eZhu, Z., Hou, J., Lyu, X.,  \n*[Learning Graph-embedded Key-event Back-tracing for Object Tracking in Event Clouds](https://openreview.net/pdf?id=hTxYJAKY85)*,  \nThirty-sixth Conference on Neural Information Processing Systems (NeurIPS), 2022. [PDF](https://openreview.net/pdf?id=hTxYJAKY85), [Code](https://github.com/ZHU-Zhiyu/Event-tracking).\n- \u003ca name=\"Elshair22opteng\"\u003e\u003c/a\u003eEl Shair, Z., Rawashdeh, S.A.,  \n*[High-temporal-resolution event-based vehicle detection and tracking](https://doi.org/10.1117/1.OE.62.3.031209)*,  \nOptical Engineering, 2022. [Dataset](http://sar-lab.net/event-based-vehicle-detection-and-tracking-dataset/).\n- \u003ca name=\"Guillen-Garcia22\"\u003e\u003c/a\u003eGuillen-Garcia, J., Palacios-Alonso, D., Cabello, E., Conde, C.,  \n*[Unsupervised adaptive multi-object tracking-by-clustering algorithm with a bio-inspired system](https://doi.org/10.1109/ACCESS.2022.3154895)*,  \nIEEE Access, 2022.\n- \u003ca name=\"Messikommer23cvpr\"\u003e\u003c/a\u003eMessikommer, N., Fang, C., Gehrig, M., Scaramuzza, D.,  \n*[Data-driven Feature Tracking for Event Cameras](https://arxiv.org/abs/2211.12826)*,  \nIEEE Conf. Computer Vision and Pattern Recognition (CVPR), 2023. [PDF](https://rpg.ifi.uzh.ch/docs/CVPR23_Messikommer.pdf), [YouTube](https://youtu.be/dtkXvNXcWRY), [Code](https://github.com/uzh-rpg/deep_ev_tracker).  \n- \u003ca name=\"Pedersen23nice\"\u003e\u003c/a\u003ePedersen, J., Singhal, R., Conradt, J.,\u003cbr/\u003e\n  [Translation and Scale Invariance for Event-Based Object tracking](https://dl.acm.org/doi/10.1145/3584954.3584996),\u003cbr/\u003e\n  Proc. Annual Neuro-Inspired Computational Elements Conf. (NICE), 2023, pp. 86-91. \u003ca href=\"https://jepedersen.dk/202304_nice_object\"\u003eWebsite\u003c/a\u003e, \u003ca href=\"https://github.com/jegp/coordinate-regression\"\u003ecode\u003c/a\u003e, \u003ca href=\"https://jepedersen.dk/slides/2304_NICE/2304_object_tracking.html\"\u003epresentation\u003c/a\u003e.\n- \u003ca name=\"Zhu23iccv\"\u003e\u003c/a\u003eZhu, Z., Hou, J., Wu DO.,\u003cbr/\u003e\n*[Cross-modal Orthogonal High-rank Augmentation for RGB-Event Transformer-trackers](https://arxiv.org/abs/2307.04129).*,\u003cbr/\u003e\nIEEE Int. Conf. Computer Vision (ICCV), 2023., [Code](https://github.com/ZHU-Zhiyu/High-Rank_RGB-Event_Tracker).\n- \u003ca name=\"Nagaraj23icra\"\u003e\u003c/a\u003eNagaraj, M., Liyanagedera, C.M., Roy, K.,\u003cbr/\u003e\n*[DOTIE - Detecting Objects through Temporal Isolation of Events using a Spiking Architecture](https://ieeexplore.ieee.org/abstract/document/10161164).*,\u003cbr/\u003e\nIEEE Int. Conf. Robotics and Automation (ICRA), 2023. [Arxiv](https://arxiv.org/abs/2210.00975), [CVPR 2023 workshop](https://tub-rip.github.io/eventvision2023/papers/2023CVPRW_Live_Demonstration_Real-time_Event-based_Speed_Detection_using_Spiking_Neural_Networks.pdf), [Code](https://github.com/manishnagaraj/DOTIE).\n- [Gao et al., ICCV 2023](#Gao23iccv), *A 5-Point Minimal Solver for Event Camera Relative Motion Estimation*.\n    - [Gao et al., CVPR 2024](#Gao24cvpr), *An N-Point Linear Solver for Line and Motion Estimation with Event Cameras*.\n- \u003ca name=\"Li24cvpr\"\u003e\u003c/a\u003eLi, S., Zhou, Z., Xue, Z., Li, Y., Du, S., Gao, Y.,\u003cbr/\u003e\n  *3D Feature Tracking via Event Camera*,\u003cbr/\u003e\n  IEEE Conf. Computer Vision and Pattern Recognition (CVPR), 2024. [Code](https://github.com/lisiqi19971013/E-3DTrack), [Dataset](https://github.com/lisiqi19971013/event-based-datasets).\n- \u003ca name=\"Kang24icra\"\u003e\u003c/a\u003eKang, Y., Caron, G., Ishikawa, R., Escande, A., Chappellet, K., Sagawa, R., Oishi, T.,\u003cbr/\u003e\n*[Direct 3D model-based object tracking with event camera by motion interpolation](https://www.cvl.iis.u-tokyo.ac.jp/~kyf/ICRA2024/BIAM.pdf).*,\u003cbr/\u003e\nIEEE Int. Conf. Robotics and Automation (ICRA), 2024. [Dataset](https://www.cvl.iis.u-tokyo.ac.jp/~kyf/ICRA2024/).\n- \u003ca name=\"Wang24tro\"\u003e\u003c/a\u003eWang, Z., Molloy, T., van Goor, P., Mahony, R.,\u003cbr/\u003e\n*[Asynchronous Blob Tracker for Event Cameras](https://doi.org/10.1109/TRO.2024.3454410).*,\u003cbr/\u003e\nIEEE Trans. Robot. (TRO), 2024. [PDF](https://arxiv.org/pdf/2307.10593.pdf), [Video](https://www.youtube.com/watch?v=L_wJjhcToOU), [Project page](https://github.com/ziweiWWANG/AEB-Tracker).\n- \u003ca name=\"Ikura24iros\"\u003e\u003c/a\u003eIkura, M., Gentil, L. C., Müller, G. M., Schuler, F., Yamashita, A., Stürzl, W.,  \n*[RATE: Real-time Asynchronous Feature Tracking with Event Cameras](https://doi.org/10.1109/IROS58592.2024.10802050).*,  \nIEEE/RSJ Int. Conf. Intelligent Robots and Systems (IROS), 2024. [PDF](https://www.robot.t.u-tokyo.ac.jp/~yamashita/paper/B/B320Final.pdf), [Code](https://github.com/mikihiroikura/RATE).\n- \u003ca name=\"Ikura25iccvw\"\u003e\u003c/a\u003eIkura, M., Glover, A., Mizuno, M., Bartolozzi, C.,  \n*[Lattice-allocated Real-time Line Segment Feature Detection and Tracking Using Only an Event-based Camera](https://openaccess.thecvf.com/content/ICCV2025W/NeVi/html/Ikura_Lattice-allocated_Real-time_Line_Segment_Feature_Detection_and_Tracking_Using_Only_ICCVW_2025_paper.html).*,  \nIEEE/CVF Int. Conf. Computer Vision (ICCV) Workshop on Neuromorphic Vision (NeVi), 2025. [PDF](https://arxiv.org/pdf/2510.06829), [Code](https://github.com/event-driven-robotics/RT-EvLDT), [Dataset](https://zenodo.org/records/17299174)\n- \u003ca name=\"Burkhardt25iccv\"\u003e\u003c/a\u003eBurkhardt, Y., Schaefer, S., Leutenegger, S.  \n*[SuperEvent: Cross-Modal Learning of Event-based Keypoint Detection for SLAM](https://openaccess.thecvf.com/content/ICCV2025/html/Burkhardt_SuperEvent_Cross-Modal_Learning_of_Event-based_Keypoint_Detection_for_SLAM_ICCV_2025_paper.html).*,  \nIEEE/CVF Int. Conf. Computer Vision (ICCV), 2025. [PDF](https://arxiv.org/pdf/2504.00139), [YouTube](https://youtu.be/YWBr8oChfDE?si=DnR1gnQ-MSbFl7Ru), [Code](https://github.com/ethz-mrl/SuperEvent), [Project page](https://ethz-mrl.github.io/SuperEvent/)\n\n\u003ca name=\"corner-detection\"\u003e\u003c/a\u003e\n### Corner Detection and Tracking\n- \u003ca name=\"Clady15neunet\"\u003e\u003c/a\u003eClady, X., Ieng, S.-H., Benosman, R.,  \n*[Asynchronous event-based corner detection and matching](https://doi.org/10.1016/j.neunet.2015.02.013)*,  \nNeural Networks (2015), 66:91-106. \n- \u003ca name=\"Vasco16iros\"\u003e\u003c/a\u003eVasco, V., Glover, A., Bartolozzi, C.,  \n*[Fast event-based Harris corner detection exploiting the advantages of event-driven cameras](https://doi.org/10.1109/IROS.2016.7759610)*,  \nIEEE/RSJ Int. Conf. Intelligent Robots and Systems (IROS), 2016, pp. 4144-4149. [YouTube](https://youtu.be/YkI7AfBDBKE), [Code](https://github.com/robotology/event-driven)\n- \u003ca name=\"Mueggler17bmvc\"\u003e\u003c/a\u003eMueggler, E., Bartolozzi, C., Scaramuzza, D.,  \n*[Fast Event-based Corner Detection](http://rpg.ifi.uzh.ch/docs/BMVC17_Mueggler.pdf)*,  \nBritish Machine Vision Conf. (BMVC), 2017. [YouTube](https://youtu.be/tgvM4ELesgI), [Code](https://github.com/uzh-rpg/rpg_corner_events)\n    - \u003ca name=\"Liu19cvprw\"\u003e\u003c/a\u003eLiu, H., Kao, W.-T., Delbruck, T.,  \n*[Live Demonstration: A Real-time Event-based Fast Corner Detection Demo based on FPGA](http://openaccess.thecvf.com/content_CVPRW_2019/papers/EventVision/Liu_Live_Demonstration_A_Real-Time_Event-Based_Fast_Corner_Detection_Demo_Based_CVPRW_2019_paper.pdf)*,  \nIEEE Conf. Computer Vision and Pattern Recognition Workshops (CVPRW), 2019.\n    - Standalone Rust implementation, [Code](https://github.com/ac-freeman/dvs-fast-corners)\n- \u003ca name=\"Alzugaray18ral\"\u003e\u003c/a\u003eAlzugaray, I., Chli, M.,  \n*[Asynchronous Corner Detection and Tracking for Event Cameras in Real Time](http://dx.doi.org/10.1109/LRA.2018.2849882)*,  \nIEEE Robotics and Automation Letters (RA-L), 3(4):3177-3184, Oct. 2018.  [PDF](https://doi.org/10.3929/ethz-b-000277131), [YouTube](https://youtu.be/bKUAZ7IQcf0), [Code](https://github.com/ialzugaray/arc_star_ros).\n- \u003ca name=\"Alzugaray183dv\"\u003e\u003c/a\u003eAlzugaray, I., Chli, M.,  \n*[ACE: An Efficient Asynchronous Corner Tracker for Event Cameras](https://doi.org/10.1109/3DV.2018.00080)*,  \nIEEE Int. Conf. 3D Vision (3DV), 2018. [PDF](https://doi.org/10.3929/ethz-b-000291763), [YouTube](https://youtu.be/I31yQqmCsfs)\n- \u003ca name=\"Scheerlinck19ral\"\u003e\u003c/a\u003eScheerlinck, C., Barnes, N., Mahony, R.,  \n*[Asynchronous Spatial Image Convolutions for Event Cameras](https://doi.org/10.1109/LRA.2019.2893427)*,  \nIEEE Robotics and Automation Letters (RA-L), 4(2):816-822, Apr. 2019.  [PDF](https://cedric-scheerlinck.github.io/files/2018_event_convolutions.pdf), [Website](https://cedric-scheerlinck.github.io/2018_event_convolutions)\n- \u003ca name=\"Manderscheid19cvpr\"\u003e\u003c/a\u003eManderscheid, J., Sironi, A., Bourdis, N., Migliore, D., Lepetit, V.,  \n*[Speed Invariant Time Surface for Learning to Detect Corner Points with Event-Based Cameras](http://openaccess.thecvf.com/content_CVPR_2019/html/Manderscheid_Speed_Invariant_Time_Surface_for_Learning_to_Detect_Corner_Points_CVPR_2019_paper.html)*,  \nIEEE Conf. Computer Vision and Pattern Recognition (CVPR), 2019.  [PDF](https://arxiv.org/pdf/1903.11332)\n- \u003ca name=\"Manderscheid19cvpr\"\u003e\u003c/a\u003eLi, R., Shi, D., Zhang, Y., Li, K., Li, R.,  \n*[FA-Harris: A Fast and Asynchronous Corner Detector for Event Cameras](https://doi.org/10.1109/IROS40897.2019.8968491)*,  \nIEEE/RSJ Int. Conf. Intelligent Robots and Systems (IROS), 2019. [PDF](https://arxiv.org/pdf/1906.10925)\n- \u003ca name=\"Mohamed20icpr\"\u003e\u003c/a\u003eMohamed, S. A. S., Yasin, J. N., Haghbayan, M.-H., Miele, A., Heikkonen, J., Tenhunen, H., Plosila, J.,  \n*[Dynamic Resource-aware Corner Detection for Bio-inspired Vision Sensors](https://arxiv.org/pdf/2010.15507)*,  \nInt. Conf. Pattern Recognition (ICPR), 2020.\n- \u003ca name=\"Mohamed20isvc\"\u003e\u003c/a\u003eMohamed, S. A. S., Yasin, J. N., Haghbayan, M.-H., Miele, A., Heikkonen, J., Tenhunen, H., Plosila, J.,  \n*[Asynchronous Corner Tracking Algorithm based on Lifetime of Events for DAVIS Cameras](https://arxiv.org/pdf/2010.15510)*,  \nInt. Symposium on Visual Computing (ISVC), 2020.\n- \u003ca name=\"Yilmaz21ji\"\u003e\u003c/a\u003eYılmaz, Ö., Simon-Chane, C., Histace A.,     \n*[Evaluation of Event-Based Corner Detectors ](https://doi.org/10.3390/jimaging7020025)*,  \nJ. Imaging, 2021.\n- \u003ca name=\"Chiberre21cvprw\"\u003e\u003c/a\u003eChiberre, P., Perot, E., Sironi, A., Lepetit, V.,  \n*[Detecting Stable Keypoints From Events Through Image Gradient Prediction](https://openaccess.thecvf.com/content/CVPR2021W/EventVision/papers/Chiberre_Detecting_Stable_Keypoints_From_Events_Through_Image_Gradient_Prediction_CVPRW_2021_paper.pdf)*,  \nIEEE Conf. Computer Vision and Pattern Recognition Workshops (CVPRW), 2021. [YouTube](https://youtu.be/Rrkwxp8J18c).\n- \u003ca name=\"Chui21arxiv\"\u003e\u003c/a\u003eChui, J., Klenk, S., Cremers, D.,  \n*[Event-Based Feature Tracking in Continuous Time with Sliding Window Optimization](https://arxiv.org/pdf/2107.04536)*,  \narXiv preprint arXiv, 2021.\n- \u003ca name=\"glover21tpami\"\u003e\u003c/a\u003eGlover A, Dinale A, De Souza Rosa L, Bamford S, Bartolozzi C   \n*[luvharris: A practical corner detector for event-cameras](https://doi.org/10.1109/TPAMI.2021.3135635)*,  \nIEEE Trans. Pattern Anal. Mach. Intell. (TPAMI), 2021. [Code](https://github.com/robotology/event-driven)\n- \u003ca name=\"Sengupta21ciss0\"\u003e\u003c/a\u003eSengupta, J. P., Villemur, M., Andreou, A. G.,  \n*[Efficient, event-driven feature extraction and unsupervised object tracking for embedded applications](https://doi.org/10.1109/CISS50987.2021.9400234)*,  \n55th Annual Conf. on Information Sciences and Systems (CISS), 2021.\n- [Alzugaray, I., Ph.D. Thesis, 2022](#Alzugaray22PhD),  \n*Event-driven Feature Detection and Tracking for Visual SLAM*.\n- \u003ca name=\"gava2022arxiv\"\u003e\u003c/a\u003eGava L, Monforte M, Iacono M, Bartolozzi C, Glover A   \n*[Puck: Parallel surface and convolution-kernel tracking for event-based cameras](https://arxiv.org/pdf/2205.07657)*,  \narXiv preprint arXiv, 2022. [Code](https://github.com/lunagava/study-air-hockey/tree/master)\n- \u003ca name=\"Freeman23mmsys\"\u003e\u003c/a\u003eFreeman, A., Mayer-Patel, K., Singh, M.,  \n*[Accelerated Event-Based Feature Detection and Compression for Surveillance Video Systems](https://doi.org/10.1145/3625468.3647618)*,  \nACM Multimedia Systems (MMSys), 2024. [PDF](https://arxiv.org/pdf/2312.08213.pdf), [Code](https://github.com/ac-freeman/adder-codec-rs).\n- \u003ca name=\"Sun24icassp\"\u003e\u003c/a\u003eSun PSV, Glover A, Bartolozzi C, Basu A   \n*[Memory Efficient Corner Detection for Event-Driven Dynamic Vision Sensors](https://ieeexplore.ieee.org/abstract/document/10445937)*,  \nInt. Conf. on Acoustics, Speech and Signal Proc. (ICASSP), 2024.\n\n\u003ca name=\"particle-detection\"\u003e\u003c/a\u003e\n### Particle Detection and Tracking\n- \u003ca name=\"Drazen11eif\"\u003e\u003c/a\u003eDrazen, D., Lichtsteiner, P., Haefliger, P., Delbruck, T., Jensen, A.,  \n*[Toward real-time particle tracking using an event-based dynamic vision sensor](https://doi.org/10.1007/s00348-011-1207-y)*,  \nExperiments in Fluids (2011), 51(1):1465-1469. [PDF](http://www.zora.uzh.ch/60624/1/Drazen_EIF_2011.pdf)\n- \u003ca name=\"Ni11jmcro\"\u003e\u003c/a\u003eNi, Z., Pacoret, C., Benosman, R., Ieng, S., Regnier, S.,  \n*[Asynchronous event-based high speed vision for microparticle tracking](http://doi.org/10.1111/j.1365-2818.2011.03565.x)*,  \nJ. Microscopy (2011), 245(3):236-244. \n- \u003ca name=\"Borer14isfv\"\u003e\u003c/a\u003eBorer, D., Roesgen, T.,  \n*[Large-scale Particle Tracking with Dynamic Vision Sensors](https://www.research-collection.ethz.ch/handle/20.500.11850/86729)*,  \nISFV16 - 16th Int. Symp. Flow Visualization, Okinawa 2014. [Project page](http://www.ifd.mavt.ethz.ch/research/group-roesgen/dynamic-vision-sensors.html), [Poster](http://www.ifd.mavt.ethz.ch/content/dam/ethz/special-interest/mavt/fluid-dynamics/ifd-dam/research/documents/posters/experimental-methods/daniel_borer_dynamic_vision_sensor.pdf)\n- \u003ca name=\"Wang20eccv\"\u003e\u003c/a\u003eWang, Y., Idoughi, R., Heidrich, W.,  \n*[Stereo Event-based Particle Tracking Velocimetry for 3D Fluid Flow Reconstruction](https://www.ecva.net/papers/eccv_2020/papers_ECCV/papers/123740035.pdf)*,  \nEuropean Conf. Computer Vision (ECCV), 2020. [Suppl. Mat.](https://www.ecva.net/papers/eccv_2020/papers_ECCV/papers/123740035-supp.zip)\n\n\n\u003ca name=\"eye_tracking\"\u003e\u003c/a\u003e\n### Eye Tracking\n- \u003ca name=\"Ryan20arxiv\"\u003e\u003c/a\u003eRyan, C., Sullivan, B. O., Elrasad, A., Lemley, J., Kielty., P., Posch, C., Perot, E.,  \n*[Real-Time Face \u0026 Eye Tracking and Blink Detection using Event Cameras](https://arxiv.org/pdf/2010.08278)*,  \narXiv, 2020.\n- \u003ca name=\"Angelopoulos20arxiv\"\u003e\u003c/a\u003eAngelopoulos, A.N., Martel, J.N.P., Kohli, A.P.S., Conradt, J., Wetzstein, G.,  \n*[Event Based, Near-Eye Gaze Tracking Beyond 10,000Hz](https://arxiv.org/pdf/2004.03577)*,  \nIEEE Trans. Vis. Comput. Graphics (Proc. VR), 2021. [YouTube](https://youtu.be/-7EneYIfinM), [Dataset](https://github.com/aangelopoulos/event_based_gaze_tracking), [Project page](http://www.computationalimaging.org/publications/event-based-eye-tracking/)\n- \u003ca name=\"Chen23biocas\"\u003e\u003c/a\u003eChen, Q., Wang, Z., Liu, S.-C., Gao, C.,  \n*[3ET: Efficient Event-based Eye Tracking using a Change-Based ConvLSTM Network](https://arxiv.org/abs/2308.11771)*,  \nIEEE BioCAS Conf., 2023. [YouTube](https://www.youtube.com/watch?v=aRB5mDNfrHM), [Code](https://github.com/qinche106/cb-convlstm-eyetracking)\n- \u003ca name=\"Wang24cvprw\"\u003e\u003c/a\u003eWang, Z., Gao, C., Wu, Z., Conde, M., Timofte, R., Liu, S.-C., Chen, Q., et al.  \n*[Event-based Eye Tracking. AIS 2024 Challenge Survey](https://arxiv.org/abs/2404.11770)*,\nIEEE Conf. Computer Vision and Pattern Recognition Workshops (CVPRW), 2024. [Challenge page](https://eetchallenge.github.io/EET.github.io/), [Code](https://github.com/EETChallenge/challenge_demo_code), [Kaggle page](https://www.kaggle.com/competitions/event-based-eye-tracking-ais2024)\n- \u003ca name=\"Bonazzi24cvprw\"\u003e\u003c/a\u003eBonazzi, P., Bian, S., Lippolis, G., Sheik, S., Magno, M.  \n*[Retina: Low-Power Eye Tracking with Event Camera and Spiking Hardware](https://arxiv.org/pdf/2312.00425)*,  \nIEEE Conf. Computer Vision and Pattern Recognition Workshops (CVPRW), 2024. [Dataset](https://pietrobonazzi.com/projects/retina), [Code](https://github.com/pbonazzi/retina), [PDF](https://arxiv.org/pdf/2312.00425).\n- \u003ca name=\"Vullers24icvse\"\u003e\u003c/a\u003eVullers Y, Gava L, Glover A, Bartolozzi C   \n*[Towards Low-power, High-frequency Gaze Direction Tracking with an Event-camera](https://github.com/event-driven-robotics/workbook_yvonne-vullers)*,  \nEuropean Conf. Comp. Vision (ECCV) Workshop on Eyes of the Future: Integrating Computer Vision in Smart Eyewear (ICVSE), 2024. [Code](https://github.com/event-driven-robotics/workbook_yvonne-vullers)\n- \u003ca name=\"Sen24imwut\"\u003e\u003c/a\u003eSen, A., Bandara, N.S., Gokarn, I., Kandappu, T., Misra, A.  \n*[EyeTrAES: Fine-grained, Low-Latency Eye Tracking via Adaptive Event Slicing](https://dl.acm.org/doi/abs/10.1145/3699745)*,  \nProceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies (IMWUT), 2024. [Code](https://github.com/arghasen10/EyeTrAES), [PDF](https://dl.acm.org/doi/pdf/10.1145/3699745).\n- \u003ca name=\"Bandara24neurips\"\u003e\u003c/a\u003eBandara, N., Kandappu, T., Sen, A., Gokarn, I., Misra, A.  \n*[EyeGraph: Modularity-aware Spatio Temporal Graph Clustering for Continuous Event-based Eye Tracking](https://openreview.net/forum?id=YxuuzyplFZ)*,  \nAdvances in Neural Information Processing Systems (NeurIPS) Datasets and Benchmarks Track, 2024. [Project Page](https://eye-tracking-for-physiological-sensing.github.io/eyegraph/), [PDF](https://openreview.net/pdf?id=YxuuzyplFZ), [Supplementary Materials](https://openreview.net/attachment?id=YxuuzyplFZ\u0026name=supplementary_material).\n- \u003ca name=\"Iddrisu24eccv\"\u003e\u003c/a\u003eIddrisu, K., Shariff, W., O’Connor, N. E., Lemley, J., Little, S.,  \n*[Evaluating Image-Based Face and Eye Tracking with Event Cameras](https://doi.org/10.1007/978-3-031-92460-6_14)*,  \nEuropean Conference on Computer Vision (ECCV), 2024, pp. 224–240. [PDF](https://arxiv.org/pdf/2408.10395?)\n- \u003ca name=\"Iddrisu24icp\"\u003e\u003c/a\u003eIddrisu, K., Shariff, W., Little, S.,  \n*[A Framework for Pupil Tracking with Event Cameras](https://doi.org/10.1049/icp.2024.3288)*,  \nIET Conference Proceedings CP887, vol. 2024, no. 10, pp. 87–94.\n\n\u003ca name=\"optical-flow-estimation\"\u003e\u003c/a\u003e\n## Optical Flow Estimation\n- \u003ca name=\"Benosman12neunet\"\u003e\u003c/a\u003eDelbruck, T.,  \n*[Frame-free dynamic digital vision](https://www.research-collection.ethz.ch/handle/20.500.11850/81769),*  \nInt. Symp. on Secure-Life Electronics, Advanced Electronics for Quality Life and Society, pp. 21-26, 2008. [PDF](www.ini.uzh.ch/admin/extras/doc_get.php?id=42508)\n- [Cook et al., IJCNN 2011](#Cook11ijcnn),  \n*Interacting maps for fast visual interpretation*.  (Joint estimation of optical flow, image intensity and angular velocity with a rotating event camera).\n- \u003ca name=\"Benosman12neunet\"\u003e\u003c/a\u003eBenosman, R., Ieng, S.-H., Clercq, C., Bartolozzi, C., Srinivasan, M.,  \n*[Asynchronous Frameless Event-Based Optical Flow](https://doi.org/10.1016/j.neunet.2011.11.001),*  \nNeural Networks (2012), 27:32-37. \n- \u003ca name=\"Orchard13biocas\"\u003e\u003c/a\u003eOrchard, G., Benosman, R., Etienne-Cummings, R., Thakor, N,  \n*[A Spiking Neural Network Architecture for Visual Motion Estimation](https://doi.org/10.1109/BioCAS.2013.6679698)*,  \nIEEE Biomedical Circuits and Systems Conf. (BioCAS), 2013. [PDF](https://www.researchgate.net/publication/261075772_A_spiking_neural_network_architecture_for_visual_motion_estimation), [Code](https://github.com/gorchard/Spiking_Motion)\n- \u003ca name=\"Benosman14tnnls\"\u003e\u003c/a\u003eBenosman, R., Clercq, C., Lagorce, X., Ieng, S.-H., Bartolozzi, C.,  \n*[Event-Based Visual Flow](https://doi.org/10.1109/TNNLS.2013.2273537),*  \nIEEE Trans. Neural Netw. Learn. Syst. (TNNLS), 25(2):407-417, 2014. [Code (jAER): LocalPlanesFlow](https://github.com/SensorsINI/jaer/blob/master/src/ch/unizh/ini/jaer/projects/rbodo/opticalflow/LocalPlanesFlow.java)\n    - [Clady et al., Front. Neurosci. 2014](#Clady14fnins),  \n    *Asynchronous visual event-based time-to-contact*.\n    - \u003ca name=\"Mueggler15icra\"\u003e\u003c/a\u003eE. Mueggler, C. Forster, N. Baumli, G. Gallego, D. Scaramuzza,  \n*[Lifetime Estimation of Events from Dynamic Vision Sensors](http://dx.doi.org/10.1109/ICRA.2015.7139876)*,  \nIEEE Int. Conf. Robotics and Automation (ICRA), 2015, pp. 4874-4881. [PDF](http://rpg.ifi.uzh.ch/docs/ICRA15_Mueggler.pdf), [PPT](http://rpg.ifi.uzh.ch/docs/ICRA15_Mueggler.pptm), [Code](https://www.github.com/uzh-rpg/rpg_event_lifetime)\n    - \u003ca name=\"Lee17iccas\"\u003e\u003c/a\u003eLee, A. J., Kim, A.,  \n*[Event-based Real-time Optical Flow Estimation](https://doi.org/10.23919/ICCAS.2017.8204333)*,  \nIEEE Int. Conf. on Control, Automation and Systems (ICCAS), 2017.\n    - \u003ca name=\"Aung18iscas\"\u003e\u003c/a\u003eAung, M.T., Teo, R., Orchard, G.,  \n*[Event-based Plane-fitting Optical Flow for Dynamic Vision Sensors in FPGA](https://doi.org/10.1109/ISCAS.2018.8351588)*,  \nIEEE Int. Symp. Circuits and Systems (ISCAS), 2018. [Code](https://github.com/gorchard/FPGA_event_based_optical_flow)\n- \u003ca name=\"Barranco14ieee\"\u003e\u003c/a\u003eBarranco, F., Fermüller, C., Aloimonos, Y.,  \n*[Contour motion estimation for asynchronous event-driven cameras](https://doi.org/10.1109/JPROC.2014.2347207)*,  \nProc. IEEE (2014), 102(10):1537-1556. [PDF](http://www.cfar.umd.edu/~fer/postscript/contourmotion-dvs-final.pdf)\n- \u003ca name=\"Lee14icip\"\u003e\u003c/a\u003eLee, J.H., Lee, K., Ryu, H., Park, P.K.J., Shin, C.W., Woo, J., Kim, J.-S.,  \n*[Real-time motion estimation based on event-based vision sensor](https://doi.org/10.1109/ICIP.2014.7025040)*,  \nIEEE Int. Conf. Image Processing (ICIP), 2014.\n- \u003ca name=\"Richter14bc\"\u003e\u003c/a\u003eRichter, C., Röhrbein, F., Conradt, J.,  \n[Bio inspired optic flow detection using neuromorphic hardware](https://doi.org/10.12751/NNCN.BC2014.0032),  \nBernstein Conf. 2014. [PDF](https://mediatum.ub.tum.de/doc/1281617/789727.pdf)\n- \u003ca name=\"Barranco15iwann\"\u003e\u003c/a\u003eBarranco, F., Fermüller, C., Aloimonos, Y.,  \n*[Bio-inspired Motion Estimation with Event-Driven Sensors](https://doi.org/10.1007/978-3-319-19258-1_27)*,  \nInt. Work-Conf. Artificial Neural Networks (IWANN) 2015, Advances in Computational Intell., pp. 309-321. [PDF](https://www.ugr.es/~fbarranco/docs/IWANN_Barranco_et_al_2015.pdf)\n- \u003ca name=\"Conradt15robio\"\u003e\u003c/a\u003eConradt, J.,  \n*[On-Board Real-Time Optic-Flow for Miniature Event-Based Vision Sensors](https://doi.org/10.1109/ROBIO.2015.7419043)*,  \nIEEE Int. Conf. Robotics and Biomimetics (ROBIO), 2015.\n- \u003ca name=\"Brosch15fnins\"\u003e\u003c/a\u003eBrosch, T., Tschechne, S., Neumann, H.,  \n*[On event-based optical flow detection](https://doi.org/10.3389/fnins.2015.00137)*,  \nFront. Neurosci. (2015), 9:137.\n    - \u003ca name=\"Tschechne14bict\"\u003e\u003c/a\u003eTschechne, S., Brosch, T., Sailer, R., von Egloffstein, N., Abdul-Kreem L.I., Neumann, H.,  \n*[On event-based motion detection and integration](http://dx.doi.org/10.4108/icst.bict.2014.257904)*,  \nInt. Conf. Bio-inspired Information and Comm. Technol. (BICT), 2014. [PDF](https://dl.acm.org/citation.cfm?id=2744588)\n    - \u003ca name=\"Tschechne14annpr\"\u003e\u003c/a\u003eTschechne, S., Sailer R., Neumann, H.,  \n*[Bio-Inspired Optic Flow from Event-Based Neuromorphic Sensor Input](https://doi.org/10.1007/978-3-319-11656-3_16)*,  \nIAPR Workshop on Artificial Neural Networks in Pattern Recognition (ANNPR) 2014, pp. 171-182.\n    - \u003ca name=\"Brosch15bict\"\u003e\u003c/a\u003eBrosch, T., Neumann, H.,  \n*[Event-based optical flow on neuromorphic hardware](https://doi.org/10.4108/eai.3-12-2015.2262447)*,  \nInt. Conf. Bio-inspired Information and Comm. Technol. (BICT), 2015. [PDF](https://dl.acm.org/citation.cfm?id=2954727)\n    - \u003ca name=\"Brosch15braincomp\"\u003e\u003c/a\u003eBrosch, T., Tschechne, S., Neumann, H.,  \n*[Visual Processing in Cortical Architecture from Neuroscience to Neuromorphic Computing](https://doi.org/10.1007/978-3-319-50862-7_7)*,  \nInt. Workshop on Brain-Inspired Computing (BrainComp), 2015. LNCS, vol 10087.\n    - \u003ca name=\"Kosiorek15techrep\"\u003e\u003c/a\u003eKosiorek, A., Adrian, D., Rausch, J., Conradt, J.,  \n*[An Efficient Event-Based Optical Flow Implementation in C/C++ and CUDA](http://tum.neurocomputing.systems/fileadmin/w00bqs/www/publications/pp/2015SS-PP-RealTimeDVSOpticFlow.pdf),*  \nTech. Rep. TU Munich, 2015.\n- [Milde et al., EBCCSP 2015](#Milde15ebccsp),  \n*Bioinspired event-driven collision avoidance algorithm based on optic flow*.\n- \u003ca name=\"Giulioni16fnins\"\u003e\u003c/a\u003eGiulioni, M., Lagorce, X., Galluppi, F., Benosman, R.,  \n*[Event-Based Computation of Motion Flow on a Neuromorphic Analog Neural Platform](https://doi.org/10.3389/fnins.2016.00035)*,  \nFront. Neurosci. (2016), 10:35. \n    - \u003ca name=\"Haessig19aicas\"\u003e\u003c/a\u003eHaessig, G., Galluppi, F., Lagorce, X., Benosman, R.,  \n*[Neuromorphic networks on the SpiNNaker platform](https://doi.org/10.1109/AICAS.2019.8771512)*,  \nIEEE Int. Conf. Artificial Intelligence Circuits and Systems (AICAS), 2019.\n- \u003ca name=\"Rueckauer16fnins\"\u003e\u003c/a\u003eRueckauer, B. and Delbruck, T.,  \n*[Evaluation of Event-Based Algorithms for Optical Flow with Ground-Truth from Inertial Measurement Sensor](https://doi.org/10.3389/fnins.2016.00176),*  \nFront. Neurosci. (2016), 10:176. [YouTube](https://youtu.be/Ji1MzE4QbM4)\n    - [Code (jAER)](https://github.com/SensorsINI/jaer/tree/master/src/ch/unizh/ini/jaer/projects/rbodo/opticalflow)\n- \u003ca name=\"Bardow16cvpr\"\u003e\u003c/a\u003eBardow, P. A., Davison, A. J., Leutenegger, S.,  \n*[Simultaneous Optical Flow and Intensity Estimation from an Event Camera](http://www.cv-foundation.org/openaccess/content_cvpr_2016/papers/Bardow_Simultaneous_Optical_Flow_CVPR_2016_paper.pdf)*,  \nIEEE Conf. Computer Vision and Pattern Recognition (CVPR), 2016. [YouTube](https://youtu.be/1zqJpiheaaI), [YouTube 2](https://youtu.be/CASsIFuPxmc), [Dataset: 4 sequences](http://wp.doc.ic.ac.uk/pb2114/datasets/)\n- \u003ca name=\"Stoffregen17acra\"\u003e\u003c/a\u003eStoffregen, T., Kleeman, L.,  \n*[Simultaneous Optical Flow and Segmentation (SOFAS) using Dynamic Vision Sensor](http://www.araa.asn.au/acra/acra2017/papers/pap127s1-file1.pdf)*,  \nAustralasian Conf. Robotics and Automation (ACRA), 2017. [PDF](https://arxiv.org/pdf/1805.12326.pdf), [YouTube](https://youtu.be/JVkQOW_iUqs)\n- \u003ca name=\"Haessig17tbcas\"\u003e\u003c/a\u003eHaessig, G., Cassidy, A. Alvarez, R., Benosman, R., Orchard, G.,  \n*[Spiking Optical Flow for Event-based Sensors Using IBM's TrueNorth Neurosynaptic System](https://doi.org/10.1109/TBCAS.2018.2834558)*,  \nIEEE Trans. Biomed. Circuits Syst., 12(4):860-870, 2018. [PDF](https://arxiv.org/pdf/1710.09820.pdf)\n- [Gallego et al., CVPR 2018](#Gallego18cvpr),  \n*A Unifying Contrast Maximization Framework for Event Cameras, with Applications to Motion, Depth and Optical Flow Estimation*.\n    - \u003ca name=\"Stoffregen19cvpr\"\u003e\u003c/a\u003eStoffregen, T., Kleeman, L.,  \n*[Event Cameras, Contrast Maximization and Reward Functions: An Analysis](http://openaccess.thecvf.com/content_CVPR_2019/html/Stoffregen_Event_Cameras_Contrast_Maximization_and_Reward_Functions_An_Analysis_CVPR_2019_paper.html)*,  \nIEEE Conf. Computer Vision and Pattern Recognition (CVPR), 2019.\n    - [Gallego et al., CVPR 2019](#Gallego19cvpr),  \n*Focus Is All You Need: Loss Functions For Event-based Vision*.\n    - [Stoffregen et al., ICCV 2019](#Stoffregen19iccv),  \n*Event-Based Motion Segmentation by Motion Compensation*.\n    - [Ghosh et al., AISY 2022](#Ghosh22aisy),  \n*Multi-Event-Camera Depth Estimation and Outlier Rejection by Refocused Events Fusion (MCEMVS)*.\n    - [Shiba et al., Sensors 2022](#Shiba22sensors),  \n*Event Collapse in Contrast Maximization Frameworks*.\n    - [Shiba et al., AISY 2022](#Shiba22aisy),  \n*A Fast Geometric Regularizer to Mitigate Event Collapse in the Contrast Maximization Framework*.\n    - [Shiba et al., ECCV 2022](#Shiba22eccv),  \n*Secrets of Event-based Optical Flow*.\n    - [Zhang et al., TPAMI 2023](#Zhang22tpami),  \n*Formulating Event-based Image Reconstruction as a Linear Inverse Problem with Deep Regularization using Optical Flow*.\n    - [Guo et al. TRO 2024](#Guo24tro),  \n*CMax-SLAM: Event-based Rotational-Motion Bundle Adjustment and SLAM System using Contrast Maximization*.\n    - [Shiba et al. TPAMI 2024](#Shiba24tpami),  \n*Secrets of Event-based Optical Flow, Depth and Ego-motion Estimation by Contrast Maximization*.\n    - [Hamann et al. ECCV 2024](#Hamann24eccv),  \n*Motion-prior Contrast Maximization for Dense Continuous-Time Motion Estimation*.\n    - [Karmokar et al. WACV 2025](#Karmokar25wacv),  \n*Secrets of Edge-Informed Contrast Maximization for Event-Based Vision*.\n- \u003ca name=\"Zhu18rss\"\u003e\u003c/a\u003eZhu, A., Yuan, L., Chaney, K., Daniilidis, K.,  \n*[EV-FlowNet: Self-Supervised Optical Flow Estimation for Event-based Cameras](http://www.roboticsproceedings.org/rss14/p62.pdf)*,  \nRobotics: Science and Systems (RSS), 2018. [PDF](https://arxiv.org/abs/1802.06898), [YouTube](https://youtu.be/eMHZBSoq0sE), [Code](https://github.com/daniilidis-group/EV-FlowNet)\n    - [Gehrig et al., ICCV 2019](#Gehrig19iccv),  \n*End-to-End Learning of Representations for Asynchronous Event-Based Data*.\n- \u003ca name=\"Liu18bmvc\"\u003e\u003c/a\u003eLiu, M., Delbruck, T.,  \n*[Adaptive Time-Slice Block-Matching Optical Flow Algorithm for Dynamic Vision Sensors](http://bmvc2018.org/contents/papers/0280.pdf)*,  \nBritish Machine Vision Conf. (BMVC), 2018. [Supplementary material](https://docs.google.com/document/d/10X0z4zznuV9j1OOjWpJGv-YCWujkF7FiYjG6efwUrP0/edit), [Video](https://youtu.be/fGJ8jyqziBI)\n    - \u003ca name=\"Liu17iscas\"\u003e\u003c/a\u003eLiu, M., Delbruck, T.,  \n*[Block-Matching Optical Flow for Dynamic Vision Sensors: Algorithm and FPGA Implementation](https://arxiv.org/pdf/1706.05415.pdf)*,  \nIEEE Int. Symp. Circuits and Systems (ISCAS), 2017.\n- \u003ca name=\"Ye20iros\"\u003e\u003c/a\u003eYe, C., Mitrokhin, A., Parameshwara, C., Fermüller, C., Yorke, J. A., Aloimonos,Y,  \n*[Unsupervised Learning of Dense Optical Flow, Depth and Egomotion with Event-Based Sensors](https://arxiv.org/pdf/1809.08625.pdf)*,  \nIEEE/RSJ Int. Conf. Intelligent Robots and Systems (IROS), 2020. [PDF](https://arxiv.org/pdf/1809.08625.pdf), [YouTube](https://youtu.be/hmDDAQVD0B0), [Project page](http://prg.cs.umd.edu/ECN.html)\n- [Seifozzakerini, Ph.D. Thesis, 2018](#Seifozzakerini18PhD),  \n*Analysis of object and its motion in event-based videos*.\n- \u003ca name=\"Nagata19iwait\"\u003e\u003c/a\u003eNagata, J., Sekikawa, Y., Hara, K., Aoki, Y.,  \n[FOE-based regularization for optical flow estimation from an in-vehicle event camera](https://doi.org/10.1117/12.2521520),  \nProc. SPIE 11049, Int. Workshop on Advanced Image Technology (IWAIT), 2019.\n- \u003ca name=\"ParedesValles19tpami\"\u003e\u003c/a\u003eParedes-Valles, F., Scheper, K. Y. W., de Croon, G. C. H. E.,  \n*[Unsupervised Learning of a Hierarchical Spiking Neural Network for Optical Flow Estimation: From Events to Global Motion Perception](https://ieeexplore.ieee.org/document/8660483)*,  \nIEEE Trans. Pattern Anal. Machine Intell. (TPAMI), 2019. [PDF](https://arxiv.org/abs/1807.10936), [YouTube](https://www.youtube.com/watch?v=FJrba02kZII\u0026list=PL_KSX9GOn2P80tm3IsgbmPAUi2KDE53zI\u0026index=2\u0026t=0s), [Code](https://github.com/tudelft/cuSNN).\n- \u003ca name=\"Zhu19cvpr\"\u003e\u003c/a\u003eZhu, A. Z., Yuan, L., Chaney, K., Daniilidis, K.,  \n*[Unsupervised Event-Based Learning of Optical Flow, Depth, and Egomotion](http://openaccess.thecvf.com/content_CVPR_2019/papers/Zhu_Unsupervised_Event-Based_Learning_of_Optical_Flow_Depth_and_Egomotion_CVPR_2019_paper.pdf)*,  \nIEEE Conf. Computer Vision and Pattern Recognition (CVPR), 2019. [PDF](https://arxiv.org/pdf/1812.08156), [YouTube](https://youtu.be/aDzFSG4yV0M), [Patent](http://www.freepatentsonline.com/y2020/0265590.html)\n    - \u003ca name=\"Zhu18eccvw\"\u003e\u003c/a\u003eZhu, A. Z., Yuan, L., Chaney, K., Daniilidis, K.,  \n*[Unsupervised Event-Based Optical Flow Using Motion Compensation](https://doi.org/10.1007/978-3-030-11024-6_54)*,  \nEuropean Conf. Computer Vision Workshops (ECCVW), 2018. [PDF](http://openaccess.thecvf.com/content_ECCVW_2018/papers/11134/Zhu_Unsupervised_Event-based_Optical_Flow_using_Motion_Compensation_ECCVW_2018_paper.pdf)\n- \u003ca name=\"Khoei19neco\"\u003e\u003c/a\u003eKhoei, M.A., Benosman, R.,  \n*[Asynchronous Event-Based Motion Processing: From Visual Events to Probabilistic Sensory Representation](https://doi.org/10.1162/neco_a_01191)*,  \nNeural Computation (2019), 31(6):1114-1138. \n- \u003ca name=\"Almatrafi19davis\"\u003e\u003c/a\u003eAlmatrafi, M. M., Hirakawa, K.,  \n*[DAViS Camera Optical Flow](http://doi.org/10.1109/TCI.2019.2948787)*,  \nIEEE Trans. Comput. Imag. (TCI), 6:396-407, 2019.\n- \u003ca name=\"Almatrafi20arxiv\"\u003e\u003c/a\u003eAlmatrafi, M., Baldwin, R., Aizawa, K., Hirakawa, K.,  \n*[Distance Surface for Event-Based Optical Flow](https://doi.org/10.1109/TPAMI.2020.2986748)*,  \nIEEE Trans. Pattern Anal. Machine Intell. (TPAMI), 2020. [PDF](https://arxiv.org/pdf/2003.12680), [Dataset](https://sites.google.com/a/udayton.edu/issl/software/dataset?authuser=0)\n- \u003ca name=\"Lee20eccv\"\u003e\u003c/a\u003eLee, C., Kosta, A., Zhu, A.Z., Chaney, K., Daniilidis, K., Roy, K.,  \n*[Spike-FlowNet: Event-based Optical Flow Estimation with Energy-Efficient Hybrid Neural Networks](https://www.ecva.net/papers/eccv_2020/papers_ECCV/papers/123740358.pdf)*,  \nEuropean Conf. Computer Vision (ECCV), 2020. [Suppl. Mat.](https://www.ecva.net/papers/eccv_2020/papers_ECCV/papers/123740358-supp.pdf), [PDF](https://arxiv.org/pdf/2003.06696)\n- \u003ca name=\"DAngelo20fnins\"\u003e\u003c/a\u003eD'Angelo, G., Janotte, E., Schoepe, T., O'Keeffe, J., Milde, M. B., Chicca, E., Bartolozzi, C.,  \n*[Event-Based Eccentric Motion Detection Exploiting Time Difference Encoding](https://doi.org/10.3389/fnins.2020.00451)*,  \nFront. Neurosci. (2020), 14:451. [Project page](https://github.com/event-driven-robotics/sEMD-iCub)\n- \u003ca name=\"Pan20cvpr\"\u003e\u003c/a\u003ePan, L., Liu, M., Hartley, R.,  \n*[Single Image Optical Flow Estimation with an Event Camera](http://openaccess.thecvf.com/content_CVPR_2020/papers/Pan_Single_Image_Optical_Flow_Estimation_With_an_Event_Camera_CVPR_2020_paper.pdf)*,  \nIEEE Conf. Computer Vision and Pattern Recognition (CVPR), 2020.\n- \u003ca name=\"Low20cvprw\"\u003e\u003c/a\u003eLow, W. F., Gao, Z., Xiang, C., Ramesh, B.,  \n[SOFEA: A Non-Iterative and Robust Optical Flow Estimation Algorithm for Dynamic Vision Sensors](http://openaccess.thecvf.com/content_CVPRW_2020/html/w6/Low_SOFEA_A_Non-Iterative_and_Robust_Optical_Flow_Estimation_Algorithm_for_CVPRW_2020_paper.html),  \nIEEE Conf. Computer Vision and Pattern Recognition Workshops (CVPRW), 2020. [PDF](http://openaccess.thecvf.com/content_CVPRW_2020/papers/w6/Low_SOFEA_A_Non-Iterative_and_Robust_Optical_Flow_Estimation_Algorithm_for_CVPRW_2020_paper.pdf), [Suppl. Mat.](http://openaccess.thecvf.com/content_CVPRW_2020/supplemental/Low_SOFEA_A_Non-Iterative_CVPRW_2020_supplemental.pdf)\n- \u003ca name=\"Akolkar20tpami\"\u003e\u003c/a\u003eAkolkar, H., Ieng, S.-H., Benosman, R.,  \n*[Real-time high speed motion prediction using fast aperture-robust event-driven visual flow](https://doi.org/10.1109/TPAMI.2020.3010468)*,  \nIEEE Trans. Pattern Anal. Machine Intell. (TPAMI), 2020. [PDF](https://arxiv.org/pdf/1811.11135)\n- \u003ca name=\"pivezhandi2020parahist\"\u003e\u003c/a\u003ePivezhandi, M., Jones, P. H., Zambreno, J.,  \n*[ParaHist: FPGA Implementation of Parallel Event-Based Histogram for Optical Flow Calculation](https://doi.org/10.1109/ASAP49362.2020.00038)*,  \nIEEE Conf. Application-specific Systems, Architectures and Processors (ASAP), 2020. [PDF](http://rcl.ece.iastate.edu/sites/default/files/papers/PivJon20A.pdf)\n- \u003ca name=\"Kepple20eccv\"\u003e\u003c/a\u003eKepple, D.R., Lee, D., Prepsius, C., Isler, V., Park, I. M., Lee, D. D.,  \n*[Jointly learning visual motion and confidence from local patches in event cameras](https://www.ecva.net/papers/eccv_2020/papers_ECCV/papers/123510494.pdf)*,  \nEuropean Conf. Computer Vision (ECCV), 2020. [Suppl. Mat.](https://www.ecva.net/papers/eccv_2020/papers_ECCV/papers/123510494-supp.pdf)\n- \u003ca name=\"Nagata21sensors\"\u003e\u003c/a\u003eNagata, J., Sekikawa, Y., Aoki, Y.,  \n*[Optical Flow Estimation by Matching Time Surface with Event-Based Cameras](https://doi.org/10.3390/s21041150)*,  \nSensors 2021, 21, 1150. [PDF](https://www.mdpi.com/1424-8220/21/4/1150/pdf)\n- [Paredes-Valles et al., CVPR 2021](#ParedesValles21cvpr),  \n*Back to Event Basics: Self-Supervised Learning of Image Reconstruction for Event Cameras via Photometric Constancy.*\n- \u003ca name=\"Hagenaars21neurips\"\u003e\u003c/a\u003eHagenaars, J. J., Paredes-Valles, F., de Croon, G. C. H. E.,  \n*[Self-Supervised Learning of Event-Based Optical Flow with Spiking Neural Networks](https://proceedings.neurips.cc/paper/2021/hash/39d4b545fb02556829aab1db805021c3-Abstract.html)*,  \nAdvances in Neural Information Processing Systems 34 (NeurIPS), 2021. [Project page](https://mavlab.tudelft.nl/event_flow/), [PDF](https://proceedings.neurips.cc/paper/2021/file/39d4b545fb02556829aab1db805021c3-Paper.pdf), [Suppl. Mat.](https://proceedings.neurips.cc/paper/2021/file/39d4b545fb02556829aab1db805021c3-Supplemental.pdf), [Code](https://github.com/tudelft/event_flow).\n- \u003ca name=\"Sikorski21cvprw\"\u003e\u003c/a\u003eSikorski, O., Izzo, D., Meoni, G.,  \n*[Event-Based Spacecraft Landing Using Time-To-Contact](https://openaccess.thecvf.com/content/CVPR2021W/AI4Space/papers/Sikorski_Event-Based_Spacecraft_Landing_Using_Time-To-Contact_CVPRW_2021_paper.pdf)*,  \nIEEE Conf. Computer Vision and Pattern Recognition Workshops (CVPRW), 2021.\n- \u003ca name=\"Peveri21cvprw\"\u003e\u003c/a\u003ePeveri, F., Testa, S., Sabatini, S. P.,  \n*[A Cortically-Inspired Architecture for Event-Based Visual Motion Processing: From Design Principles to Real-World Applications](https://openaccess.thecvf.com/content/CVPR2021W/EventVision/papers/Peveri_A_Cortically-Inspired_Architecture_for_Event-Based_Visual_Motion_Processing_From_Design_CVPRW_2021_paper.pdf)*,  \nIEEE Conf. Computer Vision and Pattern Recognition Workshops (CVPRW), 2021. [YouTube](https://youtu.be/KyS_h8i9HpM).\n- \u003ca name=\"Barbier21cvprw\"\u003e\u003c/a\u003eBarbier, T., Teuliere, C., Triesch, J.,  \n*[Spike Timing-Based Unsupervised Learning of Orientation, Disparity, and Motion Representations in a Spiking Neural Network](https://openaccess.thecvf.com/content/CVPR2021W/EventVision/papers/Barbier_Spike_Timing-Based_Unsupervised_Learning_of_Orientation_Disparity_and_Motion_Representations_CVPRW_2021_paper.pdf)*,  \nIEEE Conf. Computer Vision and Pattern Recognition Workshops (CVPRW), 2021. [Suppl.](https://openaccess.thecvf.com/content/CVPR2021W/EventVision/supplemental/Barbier_Spike_Timing-Based_Unsupervised_CVPRW_2021_supplemental.pdf), [YouTube](https://youtu.be/TL567P70L68).\n- \u003ca name=\"Gehrig21threedv\"\u003e\u003c/a\u003eGehrig, M., Millhäusler, M., Gehrig, D., Scaramuzza, D.,  \n*[E-RAFT: Dense Optical Flow from Event Cameras](https://arxiv.org/pdf/2108.10552)*,  \nIEEE Int. Conf. 3D Vision (3DV), 2021. [Code](https://github.com/uzh-rpg/E-RAFT), [Dataset](https://dsec.ifi.uzh.ch), [Youtube](https://youtu.be/dN8fl7-XfNw)\n- \u003ca name=\"Shiba22sensors\"\u003e\u003c/a\u003eShiba, S., Aoki, Y., Gallego, G.,  \n*[Event Collapse in Contrast Maximization Frameworks](https://www.mdpi.com/1424-8220/22/14/5190/htm)*,  \nSensors, 2022. [PDF](https://arxiv.org/pdf/2207.04007),  [Project page](https://github.com/tub-rip/event_collapse)\n- \u003ca name=\"Shiba24tpami\"\u003e\u003c/a\u003eShiba, S., Klose, Y., Aoki, Y., Gallego, G.,  \n*[Secrets of Event-based Optical Flow, Depth and Ego-motion Estimation by Contrast Maximization](https://doi.org/10.1109/TPAMI.2024.3396116)*,  \nIEEE Trans. Pattern Anal. Machine Intell. (TPAMI), 2024. [Project page and Code](https://github.com/tub-rip/event_based_optical_flow)\n    - \u003ca name=\"Shiba22eccv\"\u003e\u003c/a\u003eShiba, S., Aoki, Y., Gallego, G.,  \n*[Secrets of Event-based Optical Flow](https://arxiv.org/pdf/2207.10022)*,  \nEuropen Conf. Computer Vision (ECCV), 2022. [YouTube](https://youtu.be/nUb2ZRPdbWk), [Poster](https://drive.google.com/file/d/1mF-mM4teb8A9bKJJiQwN7IFsGsRIsRaX/view?usp=sharing), [Presentation at  the  PRG  Seminar Series  U. Maryland (Video)](https://vid.umd.edu/detsmediasite/Play/d31926745bdd446e8f6ce165ae4811591d), [Presentation at the GRASP Laboratory (UPenn) seminar](https://youtu.be/8v-bYCVL9hw),\n[Project page and Code](https://github.com/tub-rip/event_based_optical_flow)\n- \u003ca name=\"Shiba22spl\"\u003e\u003c/a\u003eShiba, S., Aoki, Y., Gallego, G.,  \n*[Fast Event-Based Optical Flow Estimation by Triplet Matching](https://doi.org/10.1109/LSP.2023.3234800)*,  \nIEEE Signal Process. Lett. (SPL), 29:2712-2716, 2022. [PDF](https://arxiv.org/pdf/2212.12218).\n- \u003ca name=\"Brebion21tits\"\u003e\u003c/a\u003eBrebion, V., Moreau, J., Davoine, F.,  \n*[Real-Time Optical Flow for Vehicular Perception With Low- and High-Resolution Event Cameras](https://doi.org/10.1109/TITS.2021.3136358)*,  \nIEEE Trans. Intell. Transp. Syst. (T-ITS), 2021. [PDF](https://arxiv.org/pdf/2112.10591.pdf), [Code](https://github.com/vbrebion/rt_of_low_high_res_event_cameras), [Dataset](https://datasets.hds.utc.fr/share/er2aA4R0QMJzMyO), [YouTube](https://youtube.com/playlist?list=PLLL0eWAd6OXBRXli-tB1NREdhBElAxisD).\n- \u003ca name=\"Liu22tcsvt\"\u003e\u003c/a\u003eLiu, M., Delbruck, T.,  \n*[EDFLOW: Event Driven Optical Flow Camera with Keypoint Detection and Adaptive Block Matching](https://doi.org/10.1109/TCSVT.2022.3156653)*,  \nIEEE Trans. Circuits Syst. Video Technol. (TCSVT), 32(9):5776-5789, 2022. [Preprint PDF](https://drive.google.com/file/d/15YflL00x8X1StKwZqWR3YLBN8iHAP27E/view?usp=sharing), [Code and Dataset](https://sites.google.com/view/edflow21/home)\n- \u003ca name=\"Wan22tip\"\u003e\u003c/a\u003eWan, Z., Dai, Y., Mao, Y.,  \n*[Learning Dense and Continuous Optical Flow From an Event Camera](https://doi.org/10.1109/TIP.2022.3220938)*,  \nIEEE Trans. Image Process. (TIP), 31:7237-7251, 2022. [PDF](https://arxiv.org/abs/2211.09078), [Project page](https://npucvr.github.io/DCEIFlow/), [Code](https://github.com/danqu130/DCEIFlow)\n- \u003ca name=\"Zheng22tip\"\u003e\u003c/a\u003eZheng, Y., Yu, Z., Wang, S., Huang, T.,  \n*[Spike-Based Motion Estimation for Object Tracking Through Bio-Inspired Unsupervised Learning](https://doi.org/10.1109/TIP.2022.3228168)*,  \nIEEE Trans. Image Process. (TIP), 32:335-349, 2022.\n- \u003ca name=\"Gehrig24pami\"\u003e\u003c/a\u003eGehrig, M., Muglikar, M., Scaramuzza, D.,  \n*[Dense Continuous-Time Optical Flow from Events and Frames](https://doi.org/10.1109/TPAMI.2024.3361671)*,  \nIEEE Trans. Pattern Anal. Machine Intell. (TPAMI), 2024., [PDF](https://arxiv.org/abs/2203.13674), [Code and Dataset](https://github.com/uzh-rpg/bflow)\n- \u003ca name=\"Tian22bmvc\"\u003e\u003c/a\u003eTian, Y., Andrade-Cetto, J.,  \n*[Event transformer FlowNet for optical flow estimation](https://bmvc2022.mpi-inf.mpg.de/577/)*,  \nBritish Mach. Vis. Conf., 2022, [PDF](https://bmvc2022.mpi-inf.mpg.de/0577.pdf), [Poster](https://bmvc2022.mpi-inf.mpg.de/0577_poster.pdf), [Video](https://bmvc2022.mpi-inf.mpg.de/0577_video.mp4), [Supplementary](https://bmvc2022.mpi-inf.mpg.de/0577_supp.zip).\n- [Shiba et al., TPAMI 2023](#Shiba23tpami),  \n*Even","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fuzh-rpg%2Fevent-based_vision_resources","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fuzh-rpg%2Fevent-based_vision_resources","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fuzh-rpg%2Fevent-based_vision_resources/lists"}