🔥Awesome CV Works

The post contains papers-with-code about SLAM, Pose/Object tracking, Depth/Disparity/Flow Estimation, 3D-graphic, Machine Learning, Deep Learning etc.

Here is the repo: ReadMe Card

I posted the content of the repo as follows.

  • [SLAM][ORB-SLAM3: An Accurate Open-Source Library for Visual, Visual-Inertial and Multi-Map SLAM](https://github.com/UZ-SLAMLab/ORB_SLAM3), [PDF]
  • [SLAM][LIO-SAM](https://github.com/TixiaoShan/LIO-SAM), 激光雷达IMU紧耦合SLAM
  • [Tool][Robotics Toolbox for Python](https://github.com/petercorke/robotics-toolbox-python), a Python implementation of the Robotics Toolbox for MATLAB®
  • [Matching][LISRD](https://github.com/rpautrat/LISRD),ECCV 2020, [PDF],在线局部不变特征匹配!重要!
  • [Matching][AdaLAM](https://github.com/cavalli1234/AdaLAM),特征匹配快速滤除外点
  • [Calib][fisheye_pinhole_calib_demo](https://github.com/3DCVer/fisheye_pinhole_calib_demo), 包括鱼眼模型、针孔模型的相机标定,封装了自动编译、库的打包以及外部库的调用测试
  • [Calib][SensorCalibration](https://github.com/FENGChenxi0823/SensorCalibration), IMU雷达标定
  • [VO][Low-Drift Visual Odometry in Structured Environments by Decoupling Rotational and Translational Motion](https://github.com/PyojinKim/LPVO),ICRA 2018, [PDF], 结构化环境中将旋转量与平移量进行分离优化
  • [VIO][VIO-SLAM](https://github.com/iamwangyabin/VIO-SLAM), 从零开始手写VIO课后作业
  • [Matching][TFMatch: Learning-based image matching in TensorFlow](https://github.com/lzx551402/tfmatch),TensorFlow 实现的 GeoDesc,ASLFeat以及ContextDesc
  • [Tutorial][SLAM-BOOK](https://github.com/yanyan-li/SLAM-BOOK), 一本关于SLAM的书稿,清楚的介绍SLAM系统中的使用的几何方法和深度学习方法,持续更新中
  • [Loop Closing][OverlapNet - Loop Closing for 3D LiDAR-based SLAM](https://github.com/PRBonn/OverlapNet), RSS 2020, [PDF], 3D激光雷达SLAM闭环
  • [SLAM][VDO_SLAM](https://github.com/halajun/VDO_SLAM), RGB-D相机数据作为输入,实现追踪动态物体SLAM的功能, [PDF]
  • [SLAM][orbslam-map-saving-extension](https://github.com/TUMFTM/orbslam-map-saving-extension),在ORB-SLAM的基础上增加保存+加载地图功能
  • [Tutorial][Modern Robotics: Mechanics, Planning, and Control Code Library](https://github.com/NxRLab/ModernRobotics), 现代机器人学, [Homepage]
  • [Matching][image-matching-benchmark-baselines](https://github.com/vcg-uvic/image-matching-benchmark-baselines), 图像特征匹配挑战赛主页
  • [Matching][GraphLineMatching](https://github.com/mameng1/GraphLineMatching)
  • [Matching][Locality Preserving Matching](https://github.com/jiayi-ma/LPM), IJCAI 2017, [PDF]
  • [IMU][IMUOrientationEstimator](https://github.com/ydsf16/IMUOrientationEstimator)
  • [Feature][BEBLID: Boosted Efficient Binary Local Image Descriptor](https://github.com/iago-suarez/BEBLID)
  • [Relocalization][KFNet: Learning Temporal Camera Relocalization using Kalman Filtering](https://github.com/zlthinker/KFNet),CVPR 2020,[PDF]
  • [Matching][image-matching-benchmark](https://github.com/vcg-uvic/image-matching-benchmark)
  • [Matching][GMS: Grid-based Motion Statistics for Fast, Ultra-robust Feature Correspondence](https://github.com/JiawangBian/GMS-Feature-Matcher),CVPR 17 & IJCV 19,[PDF],[Project page]
  • [Reloc][GN-Net-Benchmark](https://github.com/Artisense-ai/GN-Net-Benchmark), CVPR 2020,GN-Net: The Gauss-Newton Loss for Multi-Weather Relocalization, [PDF],[Project page]
  • [Matching][SuperGluePretrainedNetwork](https://github.com/magicleap/SuperGluePretrainedNetwork), CVPR 2020, [PDF], 划重点!2020年sota超大视角2D特征匹配,Blog
  • [Feature][D3Feat](https://github.com/XuyangBai/D3Feat), CVPR 2020, [PDF]
  • [Feature][ASLFeat](https://github.com/lzx551402/ASLFeat), CVPR 2020, ASLFeat: Learning Local Features of Accurate Shape and Localization, [PDF]
  • [Feature][GMS-Feature-Matcher](https://github.com/XuyangBai/D3Feat), CVPR 2018, GMS: Grid-based Motion Statistics for Fast, Ultra-robust Feature Correspondence, [PDF],[Project page]
  • [Feature][D3Feat](https://github.com/XuyangBai/D3Feat), CVPR 2020, [PDF]
  • [Feature][3DFeatNet](https://github.com/yewzijian/3DFeatNet), ECCV 2018, [PDF]
  • [Tutorial][AutonomousDrivingCookbook](https://github.com/microsoft/AutonomousDrivingCookbook),Scenarios, tutorials and demos for Autonomous Driving
  • [Tutorial][SLAMPaperReading](https://github.com/PaoPaoRobot/SLAMPaperReading),泡泡机器人北京线下SLAM论文分享资料
  • [Tutorial][VIO_Tutotial_Course](https://github.com/lishuwei0424/VIO_Tutotial_Course)
  • [Tutorial][VO-SLAM-Review](https://github.com/MichaelBeechan/VO-SLAM-Review)
  • [Tutorial][VINS-Mono-code-annotation](https://github.com/QingSimon/VINS-Mono-code-annotation),VINS-Mono代码注释以及公式推导
  • [Tutorial][VINS-Mono-Learning](https://github.com/ManiiXu/VINS-Mono-Learning),VINS-Mono代码注释
  • [Tutorial][VINS-Course](https://github.com/HeYijia/VINS-Course),VINS-Mono code without Ceres or ROS
  • [Tutorial][VIO-Doc](https://github.com/StevenCui/VIO-Doc),主流VIO论文推导及代码解析
  • [VO][CNN-DSO](https://github.com/muskie82/CNN-DSO), Direct Sparse Odometry with CNN Depth Prediction
  • [VO][fisheye-ORB-SLAM](https://github.com/lsyads/fisheye-ORB-SLAM), A real-time robust monocular visual SLAM system based on ORB-SLAM for fisheye cameras, without rectifying or cropping the input images
  • [VO][ORB_Line_SLAM](https://github.com/robotseu/ORB_Line_SLAM), Real-Time SLAM with BoPLW Pairs for Stereo Cameras, with Loop Detection and Relocalization Capabilities
  • [VO][DeepVO-pytorch](https://github.com/ChiWeiHsiao/DeepVO-pytorch.git), ICRA 2017 DeepVO: Towards end-to-end visual odometry with deep Recurrent Convolutional Neural Networks
  • [Calib][CamOdomCalibraTool](https://github.com/MegviiRobot/CamOdomCalibraTool), The tool to calibrate extrinsic param between camera and wheel.
  • [Calib][lidar_camera_calibration](https://github.com/heethesh/lidar_camera_calibration),another version
  • [Calib][OdomLaserCalibraTool](https://github.com/MegviiRobot/OdomLaserCalibraTool.git),相机与2D雷达标定
  • [Calib][extrinsic_lidar_camera_calibration](https://github.com/UMich-BipedLab/extrinsic_lidar_camera_calibration), LiDARTag: A Real-Time Fiducial Tag using Point Clouds, arXiv 2019, [PDF]
  • [Calib][velo2cam_calibration](https://github.com/beltransen/velo2cam_calibration), Automatic Calibration algorithm for Lidar-Stereo camera, [Project page]
  • [Dataset][IRS: A Large Synthetic Indoor Robotics Stereo Dataset for Disparity and Surface Normal Estimation](https://github.com/HKBU-HPML/IRS.git)
  • [Tools][averaging-quaternions](https://github.com/christophhagen/averaging-quaternions),四元数平均

分割线,以下是2019年的星标项目,上面是2020年新星标的。

Pose/Object tracking

Depth/Disparity & Flow estimation

3D & Graphic

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