{"id":13429972,"url":"https://github.com/tzutalin/awesome-visual-slam","last_synced_at":"2025-03-24T23:36:33.854Z","repository":{"id":37735061,"uuid":"63038123","full_name":"tzutalin/awesome-visual-slam","owner":"tzutalin","description":":books: The list of vision-based SLAM / Visual Odometry open source, blogs, and papers","archived":false,"fork":false,"pushed_at":"2022-05-10T17:57:19.000Z","size":47,"stargazers_count":2182,"open_issues_count":2,"forks_count":438,"subscribers_count":127,"default_branch":"master","last_synced_at":"2024-05-21T11:46:18.893Z","etag":null,"topics":["books","computervision","learning","point-cloud","reconstruction","ros","slam"],"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/tzutalin.png","metadata":{"files":{"readme":"README.md","changelog":null,"contributing":null,"funding":null,"license":null,"code_of_conduct":null,"threat_model":null,"audit":null,"citation":null,"codeowners":null,"security":null,"support":null}},"created_at":"2016-07-11T05:04:36.000Z","updated_at":"2024-05-19T18:01:48.000Z","dependencies_parsed_at":"2022-07-14T23:30:38.769Z","dependency_job_id":null,"html_url":"https://github.com/tzutalin/awesome-visual-slam","commit_stats":null,"previous_names":[],"tags_count":0,"template":false,"template_full_name":null,"repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/tzutalin%2Fawesome-visual-slam","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/tzutalin%2Fawesome-visual-slam/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/tzutalin%2Fawesome-visual-slam/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/tzutalin%2Fawesome-visual-slam/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/tzutalin","download_url":"https://codeload.github.com/tzutalin/awesome-visual-slam/tar.gz/refs/heads/master","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":245372215,"owners_count":20604488,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2022-07-04T15:15:14.044Z","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":["books","computervision","learning","point-cloud","reconstruction","ros","slam"],"created_at":"2024-07-31T02:00:48.691Z","updated_at":"2025-03-24T23:36:33.831Z","avatar_url":"https://github.com/tzutalin.png","language":null,"funding_links":[],"categories":["Miscellaneous","Uncategorized","优秀开源项目汇总","1. Hot SLAM Repos on GitHub","Others","Computer Vision","二 优秀开源项目汇总","Awesome-list","Other Lists","Softwares and Libraries","Disclaimer"],"sub_categories":["Other lists","Uncategorized","多相机拼接","LiDAR global localization","TeX Lists"],"readme":"# The list of vision-based SLAM / Visual Odometry open source projects, libraries, dataset, tools, and studies\n\n[![Awesome](https://cdn.rawgit.com/sindresorhus/awesome/d7305f38d29fed78fa85652e3a63e154dd8e8829/media/badge.svg)](https://github.com/tzutalin/awesome-visual-slam)\n\n## Index\n* [Libraries](#libraries)\n* [Dataset](#dataset)\n* [Tools](#tools)\n* [Projects](#projects)\n* [Learn](pages/learn.md)\n* [Miscellaneous](pages/miscellaneous.md)\n\n## Libraries\n###### Basic vision and trasformation libraries\n- [OpenCV](http://opencv.org/)\n- [Eigen](http://eigen.tuxfamily.org/index.php?title=Main_Page)\n- [Sophus](https://github.com/strasdat/Sophus)\n- [ROS](http://www.ros.org/)\n- [PointCloud](http://pointclouds.org/)\n\n###### Thread-safe queue libraries\n- [concurrentqueue](https://github.com/cameron314/concurrentqueue)\n- [Intel® TBB](https://www.threadingbuildingblocks.org/)\n- [Facebook folly PC](https://github.com/facebook/folly/blob/master/folly/ProducerConsumerQueue.h)\n\n###### Loop detection\n- [dorian3d](https://github.com/dorian3d)\n\n###### Graph Optimization\n- [ceres-solver](https://github.com/ceres-solver/ceres-solver)\n- [g2o](https://github.com/RainerKuemmerle/g2o)\n- [gtsam](https://collab.cc.gatech.edu/borg/gtsam?destination=node%2F299)\n- [Vertigo](http://openslam.org/vertigo.html)\n\n###### Map library\n- [ETHZ ASL/Grid Map](https://github.com/ethz-asl/grid_map)\n- [OmniMapper](https://github.com/CognitiveRobotics/omnimapper/wiki)\n- [OctoMap](https://github.com/OctoMap/octomap)\n\n## Dataset\n\nDataset for benchmark/test/experiment/evalutation\n\n- [TUM University](http://vision.in.tum.de/data/datasets/rgbd-dataset/download)\n- [KITTI Vision benchmark](http://www.cvlibs.net/datasets/kitti/eval_odometry.php)\n- [UNI-Freiburg](http://kaspar.informatik.uni-freiburg.de/~slamEvaluation/datasets.php)\n- [ADVIO](https://github.com/AaltoVision/ADVIO)\n- [Oxford RobotCar Dataset](https://robotcar-dataset.robots.ox.ac.uk/)\n- [HRI (Honda Research Institute) Driving Datasets](https://usa.honda-ri.com/honda-driving-datasets)\n- [Argoverse](https://www.argoverse.org/data.html)\n- [nuScenes](https://www.nuscenes.org)\n- [Waymo Open Dataset](https://waymo.com/open/)\n- [Lyft Level 5 AV Dataset 2019](https://level5.lyft.com/dataset/)\n- [KAIST Urban Dataset](https://irap.kaist.ac.kr/dataset/)\n\n## Tools\n- [rgbd-dataset tool from TUM](https://vision.in.tum.de/data/datasets/rgbd-dataset/tools)\n- [evo - evaluation tool for different trajectory formats](https://github.com/MichaelGrupp/evo)\n- [VDO_SLAM - A Visual Object-aware Dynamic SLAM library](https://github.com/halajun/vdo_slam) \n\n## Projects\n\n###### RGB (Monocular):\n\n- [Kimera](https://github.com/MIT-SPARK/Kimera). Available on ROS\n\u003e A. Rosinol, M. Abate, Y. Chang, L. Carlone. Kimera: an Open-Source Library for Real-Time Metric-Semantic Localization and Mapping. arXiv preprint arXiv:1910.02490.\n\n- [PTAM](https://github.com/Oxford-PTAM/PTAM-GPL)\n\u003e [1] Georg Klein and David Murray, \"Parallel Tracking and Mapping for Small AR Workspaces\", Proc. ISMAR 2007\n\u003e [2] Georg Klein and David Murray, \"Improving the Agility of Keyframe-based SLAM\", Proc. ECCV 2008\n\n\n- [DSO](https://github.com/JakobEngel/dso_ros). Available on ROS\n\u003eDirect Sparse Odometry, J. Engel, V. Koltun, D. Cremers, In arXiv:1607.02565, 2016\n\u003eA Photometrically Calibrated Benchmark For Monocular Visual Odometry, J. Engel, V. Usenko, D. Cremers, In arXiv:1607.02555, 2016\n\n- [LSD-SLAM](https://github.com/tum-vision/lsd_slam). Available on ROS\n\u003eLSD-SLAM: Large-Scale Direct Monocular SLAM, J. Engel, T. Schöps, D. Cremers, ECCV '14\n\u003eSemi-Dense Visual Odometry for a Monocular Camera, J. Engel, J. Sturm, D. Cremers, ICCV '13\n\n- [ORB-SLAM](https://github.com/raulmur/ORB_SLAM). Available on ROS\n\u003e [1] Raúl Mur-Artal, J. M. M. Montiel and Juan D. Tardós. ORB-SLAM: A Versatile and Accurate Monocular SLAM System. IEEE \u003e Transactions on Robotics, vol. 31, no. 5, pp. 1147-1163, 2015. (2015 IEEE Transactions on Robotics Best Paper Award). PDF.\n\u003e [2] Dorian Gálvez-López and Juan D. Tardós. Bags of Binary Words for Fast Place Recognition in Image Sequences. IEEE \u003e Transactions on Robotics, vol. 28, no. 5, pp. 1188-1197, 2012. PDF.\n\n- [Nister's Five Point Algorithm for Essential Matrix estimation, and FAST features, with a KLT tracker](https://github.com/avisingh599/mono-vo)\n\u003eD. Nister, “An efficient solution to the five-point relative pose problem,” Pattern Analysis and Machine Intelligence, IEEE Transactions on, vol. 26, no. 6, pp. 756–770, 2004.\n\n- [SVO-SLAM](https://github.com/uzh-rpg/rpg_svo). Available on ROS\n\u003e Christian Forster, Matia Pizzoli, Davide Scaramuzza, \"SVO: Fast Semi-direct Monocular Visual Odometry,\" IEEE International Conference on Robotics and Automation, 2014.\n\n###### RGB and Depth (Called RGBD):\n- [OpenCV RGBD-Odometry (Visual Odometry based RGB-D images)](https://github.com/tzutalin/OpenCV-RgbdOdometry)\n\u003e Real-Time Visual Odometry from Dense RGB-D Images, F. Steinbucker, J. Strum, D. Cremers, ICCV, 2011\n\n- [Dense Visual SLAM for RGB-D Cameras](https://github.com/tum-vision/dvo_slam). Available on ROS\n\u003e[1]Dense Visual SLAM for RGB-D Cameras (C. Kerl, J. Sturm, D. Cremers), In Proc. of the Int. Conf. on Intelligent Robot Systems (IROS), 2013.\n[2]Robust Odometry Estimation for RGB-D Cameras (C. Kerl, J. Sturm, D. Cremers), In Proc. of the IEEE Int. Conf. on Robotics and Automation (ICRA), 2013\n[3]Real-Time Visual Odometry from Dense RGB-D Images (F. Steinbruecker, J. Sturm, D. Cremers), In Workshop on Live Dense Reconstruction with Moving Cameras at the Intl. Conf. on Computer Vision (ICCV), 2011.\n\n\n- [RTAB MAP - Real-Time Appearance-Based Mapping](https://github.com/introlab/rtabmap). Available on ROS\n\u003e Online Global Loop Closure Detection for Large-Scale Multi-Session Graph-Based SLAM, 2014\n\u003e Appearance-Based Loop Closure Detection for Online Large-Scale and Long-Term Operation, 2013\n\n- [ORB2-SLAM](https://github.com/raulmur/ORB_SLAM2). Available on ROS\n\u003e [1] Raúl Mur-Artal, J. M. M. Montiel and Juan D. Tardós. ORB-SLAM: A Versatile and Accurate Monocular SLAM System. IEEE \u003e Transactions on Robotics, vol. 31, no. 5, pp. 1147-1163, 2015. (2015 IEEE Transactions on Robotics Best Paper Award).\n\u003e [2] Dorian Gálvez-López and Juan D. Tardós. Bags of Binary Words for Fast Place Recognition in Image Sequences. IEEE Transactions on Robotics, vol. 28, no. 5, pp. 1188-1197, 2012.\n\n- [InfiniTAM∞ v2](http://www.robots.ox.ac.uk/~victor/infinitam/index.html)\n\u003e Kahler, O. and Prisacariu, V.~A. and Ren, C.~Y. and Sun, X. and Torr, P.~H.~S and Murray, D.~W. Very High Frame Rate Volumetric Integration of Depth Images on Mobile Device. IEEE Transactions on Visualization and Computer Graphics (Proceedings International Symposium on Mixed and Augmented Reality 2015\n\n- [Kintinuous](https://github.com/mp3guy/Kintinuous)\n\u003e Real-time Large Scale Dense RGB-D SLAM with Volumetric Fusion, T. Whelan, M. Kaess, H. Johannsson, M.F. Fallon, J. J. Leonard and J.B. McDonald, IJRR '14\n\n- [ElasticFusion](https://github.com/mp3guy/ElasticFusion)\n\u003e [1] ElasticFusion: Real-Time Dense SLAM and Light Source Estimation, T. Whelan, R. F. Salas-Moreno, B. Glocker, A. J. Davison and S. Leutenegger, IJRR '16\n\u003e [2] ElasticFusion: Dense SLAM Without A Pose Graph, T. Whelan, S. Leutenegger, R. F. Salas-Moreno, B. Glocker and A. J. Davison, RSS '15\n\n- [Co-Fusion](http://visual.cs.ucl.ac.uk/pubs/cofusion/index.html)\n\u003e Martin Rünz and Lourdes Agapito. Co-Fusion: Real-time Segmentation, Tracking and Fusion of Multiple Objects. 2017 IEEE International Conference on Robotics and Automation (ICRA)\n\n###### RGBD and LIDAR:\n- [Google's cartographer](https://github.com/googlecartographer/cartographer). Available on ROS\n\n\n## Other open source projects\n[DynaSLAM](https://github.com/BertaBescos/DynaSLAM) A SLAM system robust in dynamic environments for monocular, stereo and RGB-D setups\n\n[openvslam](https://github.com/xdspacelab/openvslam) A Versatile Visual SLAM Framework\n\n\n## License\n\n[![CC0](http://mirrors.creativecommons.org/presskit/buttons/88x31/svg/cc-zero.svg)](https://creativecommons.org/publicdomain/zero/1.0/)\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Ftzutalin%2Fawesome-visual-slam","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Ftzutalin%2Fawesome-visual-slam","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Ftzutalin%2Fawesome-visual-slam/lists"}