diff --git a/README.md b/README.md index 865e9a5..aa179bf 100644 --- a/README.md +++ b/README.md @@ -4,18 +4,20 @@ This repository is a list of papers and open source code for 6D Object Pose Esti --- ### Vision Based + - Robust, Occlusion-aware Pose Estimation for Objects Grasped by Adaptive Hands - 2020 ICRA [[paper]](https://arxiv.org/pdf/2003.03518.pdf)[[github]](https://github.com/wenbowen123/icra20-hand-object-pose) - Multimodal Templates for Real-Time Detection of Texture-less Objects in Heavily Cluttered Scenes - 2011 [[paper]](http://campar.in.tum.de/pub/hinterstoisser2011linemod/hinterstoisser2011linemod.pdf) [[code]](http://campar.in.tum.de/pub/hinterstoisser2011linemod/hinterstoisser2011linemod.pdf) - Uncertainty-Driven 6D Pose Estimation of Objects and Scenes from a Single RGB Image - 2016 IEEE [[paper]](http://wwwpub.zih.tu-dresden.de/~cvweb/publications/papers/2016/rgbpose.pdf) ### Deep learning Based + - BundleTrack: 6D Pose Tracking for Novel Objects without Instance or Category-Level 3D Models - 2021 IROS [[paper]](https://arxiv.org/abs/2108.00516)[[github]](https://github.com/wenbowen123/BundleTrack) - bb8: A Scalable, Accurate, Robust to Partial Occlusion Method for Predicting the 3D Poses of Challenging Objects without Using Depth - 2017 ICCV [[paper]](https://arxiv.org/abs/1703.10896)[[ppt]](https://github.com/MyungHaSong/Awesome-object-pose-estimation/blob/master/bb8.pdf) - iPose: Instance-Aware 6D Pose Estimation of Partly Occluded Objects - 2017 [[paper]](https://arxiv.org/abs/1712.01924) - + - PoseCNN: A Convolutional Neural Network for 6D Object Pose Estimation in Cluttered Scenes - 2017 [[paper]](https://arxiv.org/abs/1711.00199)[[code]](https://github.com/yuxng/PoseCNN) - + - Real-Time Seamless Single Shot 6D Object Pose Prediction - 2018 [[paper]](https://arxiv.org/abs/1711.08848)[[code]](https://github.com/Microsoft/singleshotpose) - + - Deep Object Pose Estimation for Segmantic Robotic Grasping of Household Objects-2018 [[paper]](https://arxiv.org/abs/1809.10790)[[code]](https://github.com/NVlabs/Deep_Object_Pose) - Deep-6DPose: Recovering 6D Object Pose from a Single RGB Image - 2018 [[paper]](https://arxiv.org/abs/1802.10367) @@ -23,27 +25,27 @@ This repository is a list of papers and open source code for 6D Object Pose Esti - PVNet: Pixel-wise Voting Network for 6DoF Pose Estimation -2018 [[paper]](https://arxiv.org/pdf/1812.11788.pdf)[[code]](https://github.com/zju3dv/pvnet) - 6D Object Pose Estimation Based on 2D Bounding Box - 2019 WSPC [[paper]](https://arxiv.org/abs/1901.09366) - + - 6D Object Pose Estimation without PnP -2019 [[paper]](https://arxiv.org/abs/1902.01728) - + - Implicit 3D Orientation Learning for 6D Object Detection from RGB Images - 2018 ECCV [[paper]](https://arxiv.org/abs/1902.01275) - + - Normalized Object Coordinate Space for Category-Level 6D Object Pose and Size Estimation -2019 CVPR [[paper]](https://arxiv.org/abs/1901.02970)[[code]](https://github.com/hughw19/NOCS_CVPR2019) - + - DenseFusion: 6D Object Pose Estimation by Iterative Dense Fusion -2019 CVPR [[paper]](https://arxiv.org/abs/1901.04780)[[code]](https://github.com/j96w/DenseFusion)[[Code Review]](https://github.com/MyungHaSong/DenseFusion-Code-Review) - + - Segmentation-driven 6D Object Pose Estimation - 2019 CVPR [[paper]](https://arxiv.org/pdf/1812.02541.pdf)[[code]](https://github.com/cvlab-epfl/segmentation-driven-pose) - DPOD: 6D Pose Object Detector and Refiner -2019 ICCV [[paper]](https://arxiv.org/pdf/1902.11020.pdf) - + - Explaining the Ambiguity of Object Detection and 6D Pose From Visual Data -2019 ICCV[[paper]](https://arxiv.org/abs/1812.00287) - + - W-PoseNet: Dense Correspondence Regularized Pixel Pair Pose Regression - 2019 CoRL[[paper]](https://arxiv.org/pdf/1912.11888.pdf) - + - 6D Pose Estimation with Correlation Fusion - 2019 arXiv.org [[paper]](https://arxiv.org/abs/1909.12936) - + - PVN3D: A Deep Point-wise 3D Keypoints Voting Network for 6DoF Pose Estimation -2020 CVPR [[paper]](https://arxiv.org/abs/1911.04231)[[code]](https://github.com/ethnhe/PVN3D) - PFRL: Pose-Free Reinforcement Learning for 6D Pose Estimation - 2020 CVPR [[paper]](https://openaccess.thecvf.com/content_CVPR_2020/papers/Shao_PFRL_Pose-Free_Reinforcement_Learning_for_6D_Pose_Estimation_CVPR_2020_paper.pdf) - EPOS: Estimating 6D Pose of Objects with Symmetries - 2020 CVPR [[paper]](https://openaccess.thecvf.com/content_CVPR_2020/papers/Hodan_EPOS_Estimating_6D_Pose_of_Objects_With_Symmetries_CVPR_2020_paper.pdf) @@ -53,17 +55,18 @@ This repository is a list of papers and open source code for 6D Object Pose Esti - G2L-Net: Global to Local Network for Real-time 6D Pose Estimation with Embedding Vector Features 2020 CVPR [[paper]](https://openaccess.thecvf.com/content_CVPR_2020/papers/Chen_G2L-Net_Global_to_Local_Network_for_Real-Time_6D_Pose_Estimation_CVPR_2020_paper.pdf) - HybridPose: 6D Object Pose Estimation under Hybrid Representations[[paper]](https://openaccess.thecvf.com/content_CVPR_2020/papers/Song_HybridPose_6D_Object_Pose_Estimation_Under_Hybrid_Representations_CVPR_2020_paper.pdf) - Multi-Path Learning for Object Pose Estimation Across Domains[[paper]](https://openaccess.thecvf.com/content_CVPR_2020/html/Sundermeyer_Multi-Path_Learning_for_Object_Pose_Estimation_Across_Domains_CVPR_2020_paper.html) - 2020CVPR - - se(3)-TrackNet: Data-driven 6D Pose Tracking by Calibrating Image Residuals in Synthetic Domains 2020 IROS [[paper]](https://arxiv.org/abs/2007.13866) + - se(3)-TrackNet: Data-driven 6D Pose Tracking by Calibrating Image Residuals in Synthetic Domains 2020 IROS [[paper]](https://arxiv.org/abs/2007.13866) [[github]](https://github.com/wenbowen123/iros20-6d-pose-tracking) - PERCH 2.0 : Fast and Accurate GPU-based Perception via Search for Object Pose Estimation [[paper]](https://arxiv.org/abs/2008.00326) - CosyPose: Consistent multi-view multi-object 6D pose estimation ECCV 2020[[paper]](https://arxiv.org/abs/2008.08465) - - - + + + --- ## Database - LINEMOD[[link]](http://campar.in.tum.de/Main/StefanHinterstoisser) - OccludedLINEMOD[[link]](https://hci.iwr.uni-heidelberg.de/vislearn/iccv2015-occlusion-challenge/) - T-Less[[link]](http://cmp.felk.cvut.cz/t-less/) +- YCBInEOAT Dataset[[link]](https://github.com/wenbowen123/iros20-6d-pose-tracking) - YCB Video Dataset[[link]](http://www.ycbbenchmarks.com/)