mlsanityData to 14 Oct 2026

6D Object Pose Regression via Supervised Learning on Point Clouds

arXiv 2001.08942 ↗First posted 24 Jan 2020cs.CVcited by 33

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Abstract (arXiv)

This paper addresses the task of estimating the 6 degrees of freedom pose of a known 3D object from depth information represented by a point cloud. Deep features learned by convolutional neural networks from color information have been the dominant features to be used for inferring object poses, while depth information receives much less attention. However, depth information contains rich geometric information of the object shape, which is important for inferring the object pose. We use depth information represented by point clouds as the input to both deep networks and geometry-based pose refinement and use separate networks for rotation and translation regression. We argue that the axis-angle representation is a suitable rotation representation for deep learning, and use a geodesic loss function for rotation regression. Ablation studies show that these design choices outperform alternatives such as the quaternion representation and L2 loss, or regressing translation and rotation with the same network. Our simple yet effective approach clearly outperforms state-of-the-art methods on the YCB-video dataset. The implementation and trained model are avaliable at: https://github.com/GeeeG/CloudPose.

Key facts. Cited by 33 papers in the map (data through 14 Oct 2026). First posted on arXiv 24 Jan 2020.

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Citing papers per year: 2021: 4; 2022: 8; 2023: 6; 2024: 5; 2025: 7; 2026: 3.

33 papers.

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  1. 2024RGBD Objects in the Wild: Scaling Real-World 3D Object Learning from RGB-D Videoscited by 115
  2. 2021SAR-Net: Shape Alignment and Recovery Network for Category-level 6D Object Pose and Size Estimationcited by 53
  3. 2022OVE6D: Object Viewpoint Encoding for Depth-based 6D Object Pose Estimationcited by 43
  4. 2024Deep Learning-Based Object Pose Estimation: A Comprehensive Surveycited by 40
  5. 2021Deep Learning on Monocular Object Pose Detection and Tracking: A Comprehensive Overviewcited by 31
  6. 2022CPPF: Towards Robust Category-Level 9D Pose Estimation in the Wildcited by 28
  7. 2024DiffusionNOCS: Managing Symmetry and Uncertainty in Sim2Real Multi-Modal Category-level Pose Estimationcited by 25
  8. 2022Self-Supervised Geometric Correspondence for Category-Level 6D Object Pose Estimation in the Wildcited by 22
  9. 2022ES6D: A Computation Efficient and Symmetry-Aware 6D Pose Regression Frameworkcited by 19
  10. 2021StablePose: Learning 6D Object Poses from Geometrically Stable Patchescited by 17
  11. 2021CloudAAE: Learning 6D Object Pose Regression with On-line Data Synthesis on Point Cloudscited by 15
  12. 2023ViHOPE: Visuotactile In-Hand Object 6D Pose Estimation with Shape Completioncited by 14
21 more
  1. 2023GS-Pose: Category-Level Object Pose Estimation via Geometric and Semantic Correspondencecited by 12
  2. 20246DOPE-GS: Online 6D Object Pose Estimation using Gaussian Splattingcited by 11
  3. 2023Depth-based 6DoF Object Pose Estimation using Swin Transformercited by 8
  4. 2022Keypoint Cascade Voting for Point Cloud Based 6DoF Pose Estimationcited by 7
  5. 2023TransPose: 6D Object Pose Estimation with Geometry-Aware Transformercited by 7
  6. 2022CPPF++: Uncertainty-Aware Sim2Real Object Pose Estimation by Vote Aggregationcited by 6
  7. 2022Quasi-Balanced Self-Training on Noise-Aware Synthesis of Object Point Clouds for Closing Domain Gapcited by 5
  8. 2025Active 6D Pose Estimation for Textureless Objects using Multi-View RGB Framescited by 3
  9. 2025Structure-Aware Correspondence Learning for Relative Pose Estimationcited by 3
  10. 2025Joint Learning of Pose Regression and Denoising Diffusion with Score Scaling Sampling for Category-level 6D Pose Estimationcited by 1
  11. 2022Det6D: A Ground-Aware Full-Pose 3D Object Detector for Improving Terrain Robustnesscited by 0
  12. 2023TransPose: A Transformer-based 6D Object Pose Estimation Network with Depth Refinementcited by 0
  13. 2023KVN: Keypoints Voting Network with Differentiable RANSAC for Stereo Pose Estimationcited by 0
  14. 2024FastPoseCNN: Real-Time Monocular Category-Level Pose and Size Estimation Frameworkcited by 0
  15. 2025Learning Point Cloud Representations with Pose Continuity for Depth-Based Category-Level 6D Object Pose Estimationcited by 0
  16. 2025SCOPE: Semantic Conditioning for Sim2Real Category-Level Object Pose Estimation in Roboticscited by 0
  17. 2025DKPMV: Dense Keypoints Fusion from Multi-View RGB Frames for 6D Pose Estimation of Textureless Objectscited by 0
  18. 2025Equivariant symmetry-aware head pose estimation for fetal MRIcited by 0
  19. 2026Detecting 3D Line Segments for 6DoF Pose Estimation with Limited Datacited by 0
  20. 2026Rotational Symmetry based Object Pose Estimation from Point Clouds in the Absence of Known 3D Modelscited by 0
  21. 2026G6D: Geometric Learning-Free RGB-D 6D Pose Solver for Robotic Manipulationcited by 0