{"id":20062278,"url":"https://github.com/cuge1995/cvpr-2021-point-cloud-analysis","last_synced_at":"2026-02-10T06:31:00.734Z","repository":{"id":117637749,"uuid":"343614403","full_name":"cuge1995/CVPR-2021-point-cloud-analysis","owner":"cuge1995","description":"CVPR 2021 papers focusing on point cloud analysis","archived":false,"fork":false,"pushed_at":"2021-08-01T00:11:15.000Z","size":34,"stargazers_count":9,"open_issues_count":0,"forks_count":1,"subscribers_count":5,"default_branch":"main","last_synced_at":"2025-08-18T23:43:03.940Z","etag":null,"topics":["3d-point-clouds","classification","computer-vision","cvpr2021","deep-learning","detection","few-shot","paper","point-cloud","point-cloud-analysis","segmentation"],"latest_commit_sha":null,"homepage":"","language":null,"has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":"mit","status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/cuge1995.png","metadata":{"files":{"readme":"README.md","changelog":null,"contributing":null,"funding":null,"license":"LICENSE","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}},"created_at":"2021-03-02T01:56:30.000Z","updated_at":"2024-10-26T09:39:26.000Z","dependencies_parsed_at":null,"dependency_job_id":"4d35ae1e-d81e-4512-b775-f41bbc3bff55","html_url":"https://github.com/cuge1995/CVPR-2021-point-cloud-analysis","commit_stats":null,"previous_names":[],"tags_count":0,"template":false,"template_full_name":null,"purl":"pkg:github/cuge1995/CVPR-2021-point-cloud-analysis","repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/cuge1995%2FCVPR-2021-point-cloud-analysis","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/cuge1995%2FCVPR-2021-point-cloud-analysis/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/cuge1995%2FCVPR-2021-point-cloud-analysis/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/cuge1995%2FCVPR-2021-point-cloud-analysis/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/cuge1995","download_url":"https://codeload.github.com/cuge1995/CVPR-2021-point-cloud-analysis/tar.gz/refs/heads/main","sbom_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/cuge1995%2FCVPR-2021-point-cloud-analysis/sbom","scorecard":null,"host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":286080680,"owners_count":29292083,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2026-02-10T03:42:42.660Z","status":"ssl_error","status_checked_at":"2026-02-10T03:42:41.897Z","response_time":65,"last_error":"SSL_read: 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":["3d-point-clouds","classification","computer-vision","cvpr2021","deep-learning","detection","few-shot","paper","point-cloud","point-cloud-analysis","segmentation"],"created_at":"2024-11-13T13:28:16.551Z","updated_at":"2026-02-10T06:31:00.701Z","avatar_url":"https://github.com/cuge1995.png","language":null,"funding_links":[],"categories":[],"sub_categories":[],"readme":"# CVPR-2021-point-cloud-analysis\nCVPR 2021 papers focusing on point cloud analysis\n\n- [PREDATOR: Registration of 3D Point Clouds with Low Overlap](https://arxiv.org/pdf/2011.13005.pdf) `registration` `oral`\n  - [[Code](https://github.com/ShengyuH/OverlapPredator)]\n\n- [Exploring Data Efficient 3D Scene Understanding with Contrastive Scene Contexts](https://arxiv.org/pdf/2012.09165.pdf) `segmentation` `oral`\n  - [[Code](https://sekunde.github.io/project_efficient/)]\n\n- [MultiBodySync: Multi-Body Segmentation and Motion Estimation via 3D Scan Synchronization](https://arxiv.org/pdf/2101.06605.pdf) `Synchronization` `oral`\n  - [[Code](https://github.com/huangjh-pub/multibody-sync)]\n\n- [Diffusion Probabilistic Models for 3D Point Cloud Generation](https://arxiv.org/pdf/2103.01458.pdf)  `generation`\n  - [[Code](https://github.com/luost26/diffusion-point-cloud)]\n\n- [Semantic Segmentation for Real Point Cloud Scenes via Bilateral Augmentation and Adaptive Fusion, paper not yet]()\n  - [[Code](https://github.com/ShiQiu0419/BAAF-Net)]\n\n- [Towards Semantic Segmentation of Urban-Scale 3D Point Clouds: A Dataset, Benchmarks and Challenges](https://arxiv.org/pdf/2009.03137.pdf) `dataset`\n  - [[Code](https://github.com/QingyongHu/SensatUrban)]\n\n- [Few-shot 3D Point Cloud Semantic Segmentation.]() \n  - [[Code](https://github.com/Na-Z/attMPTI)]\n\n- [Bidirectional Projection Network for Cross Dimension Scene Understanding.]() `oral` `2D/3D`\n  - [[Code](https://github.com/wbhu/BPNet)]\n\n- [Self-supervised Geometric Perception.](https://arxiv.org/pdf/2103.03114.pdf) `oral` `registration`\n  - [[Code](https://github.com/theNded/SGP)]\n\n- [SpinNet: Learning a General Surface Descriptor for 3D Point Cloud Registration.](https://arxiv.org/pdf/2011.12149.pdf) `registration`\n  - [[Code](https://github.com/QingyongHu/SpinNet)]\n\n- [Style-based Point Generator with Adversarial Rendering for Point Cloud Completion.](https://arxiv.org/pdf/2103.02535.pdf)  `completion`\n  - [[Code](https://github.com/microsoft/SpareNet)]\n\n- [VRCNet: Variational Relational Point Completion Network.](https://arxiv.org/pdf/2104.10154.pdf)  `completion` `oral` `dataset`\n  - [[Code](https://github.com/paul007pl/VRCNet)]\n\n- [Cycle4Completion: Unpaired Point Cloud Completion using Cycle Transformation with Missing Region Coding.](https://arxiv.org/pdf/2103.07838.pdf) `completion`\n\n- [View-Guided Point Cloud Completion.](https://openaccess.thecvf.com/content/CVPR2021/papers/Zhang_View-Guided_Point_Cloud_Completion_CVPR_2021_paper.pdf) `completion`\n\n- [PMP-Net: Point Cloud Completion by Learning Multi-step Point Moving Paths.](https://arxiv.org/pdf/2012.03408.pdf) `completion`\n\n- [Point 4D Transformer Networks for Spatio-Temporal Modeling in Point Cloud Videos.](https://hehefan.github.io/pdfs/p4transformer.pdf)  `point cloud video` `oral`\n\n- [3D AffordanceNet: A Benchmark for Visual Object Affordance Understanding.](https://arxiv.org/pdf/2103.16397.pdf)  `Affordance estimation` `new task` `dataset`\n  - [[Code](https://github.com/Gorilla-Lab-SCUT/AffordanceNet)]\n\n- [3DIoUMatch: Leveraging IoU Prediction for Semi-Supervised 3D Object Detection.](https://arxiv.org/pdf/2012.04355v2.pdf)  `detection` \n  - [[Code](https://github.com/thu17cyz/3DIoUMatch)]\n\n- [Cylindrical and Asymmetrical 3D Convolution Networks for LiDAR-based Perception.](https://openaccess.thecvf.com/content/CVPR2021/papers/Zhu_Cylindrical_and_Asymmetrical_3D_Convolution_Networks_for_LiDAR_Segmentation_CVPR_2021_paper.pdf)  `oral` `segmentation`\n  - [[Code](https://github.com/xinge008/Cylinder3D)]\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fcuge1995%2Fcvpr-2021-point-cloud-analysis","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fcuge1995%2Fcvpr-2021-point-cloud-analysis","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fcuge1995%2Fcvpr-2021-point-cloud-analysis/lists"}