mlsanityData to 7 Oct 2026

Self-supervised 6D Object Pose Estimation for Robot Manipulation

arXiv 1909.10159 ↗First posted 23 Sep 2019cs.ROcited by 100

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Abstract (arXiv)

To teach robots skills, it is crucial to obtain data with supervision. Since annotating real world data is time-consuming and expensive, enabling robots to learn in a self-supervised way is important. In this work, we introduce a robot system for self-supervised 6D object pose estimation. Starting from modules trained in simulation, our system is able to label real world images with accurate 6D object poses for self-supervised learning. In addition, the robot interacts with objects in the environment to change the object configuration by grasping or pushing objects. In this way, our system is able to continuously collect data and improve its pose estimation modules. We show that the self-supervised learning improves object segmentation and 6D pose estimation performance, and consequently enables the system to grasp objects more reliably. A video showing the experiments can be found at https://youtu.be/W1Y0Mmh1Gd8.

Key facts. Cited by 100 papers in the map (data through 7 Oct 2026). First posted on arXiv 23 Sep 2019.

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2021: 17; 2022: 24; 2023: 20; 2024: 18; 2025: 15; 2026: 6.

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  1. 2021CLIPort: What and Where Pathways for Robotic Manipulationcited by 617
  2. 2022Perceiver-Actor: A Multi-Task Transformer for Robotic Manipulationcited by 545
  3. 2021Contact-GraspNet: Efficient 6-DoF Grasp Generation in Cluttered Scenescited by 213
  4. 2022RelPose: Predicting Probabilistic Relative Rotation for Single Objects in the Wildcited by 102
  5. 2022GPV-Pose: Category-level Object Pose Estimation via Geometry-guided Point-wise Votingcited by 94
  6. 2023RoboTAP: Tracking Arbitrary Points for Few-Shot Visual Imitationcited by 88
  7. 2022Zero-Shot Category-Level Object Pose Estimationcited by 57
  8. 2022Equivariant Descriptor Fields: SE(3)-Equivariant Energy-Based Models for End-to-End Visual Robotic Manipulation Learningcited by 54
  9. 2021SAR-Net: Shape Alignment and Recovery Network for Category-level 6D Object Pose and Size Estimationcited by 53
  10. 2023GenPose: Generative Category-level Object Pose Estimation via Diffusion Modelscited by 47
  11. 2021O2O-Afford: Annotation-Free Large-Scale Object-Object Affordance Learningcited by 46
  12. 2022Visual Reinforcement Learning with Self-Supervised 3D Representationscited by 45
38 more
  1. 2022Equivariant Transporter Networkcited by 44
  2. 2022RBP-Pose: Residual Bounding Box Projection for Category-Level Pose Estimationcited by 43
  3. 2023DeformGS: Scene Flow in Highly Deformable Scenes for Deformable Object Manipulationcited by 42
  4. 2022SSP-Pose: Symmetry-Aware Shape Prior Deformation for Direct Category-Level Object Pose Estimationcited by 41
  5. 2023IST-Net: Prior-free Category-level Pose Estimation with Implicit Space Transformationcited by 40
  6. 2023Learning Object State Changes in Videos: An Open-World Perspectivecited by 36
  7. 2024Deep Generative Models in Robotics: A Survey on Learning from Multimodal Demonstrationscited by 35
  8. 2024AffordDP: Generalizable Diffusion Policy with Transferable Affordancecited by 35
  9. 2022Occlusion-Aware Self-Supervised Monocular 6D Object Pose Estimationcited by 34
  10. 2024Fourier Transporter: Bi-Equivariant Robotic Manipulation in 3Dcited by 32
  11. 2025GraspGen: A Diffusion-based Framework for 6-DOF Grasping with On-Generator Trainingcited by 32
  12. 2021Deep Learning on Monocular Object Pose Detection and Tracking: A Comprehensive Overviewcited by 31
  13. 2022TexPose: Neural Texture Learning for Self-Supervised 6D Object Pose Estimationcited by 23
  14. 2022Visuomotor Control in Multi-Object Scenes Using Object-Aware Representationscited by 21
  15. 2021DemoGrasp: Few-Shot Learning for Robotic Grasping with Human Demonstrationcited by 20
  16. 2022Sim-to-Real 6D Object Pose Estimation via Iterative Self-training for Robotic Bin Pickingcited by 20
  17. 2021PoseContrast: Class-Agnostic Object Viewpoint Estimation in the Wild with Pose-Aware Contrastive Learningcited by 19
  18. 2022Learning 6-DoF Object Poses to Grasp Category-level Objects by Language Instructionscited by 19
  19. 2023ReorientDiff: Diffusion Model based Reorientation for Object Manipulationcited by 19
  20. 2023Leveraging Symmetries in Pick and Placecited by 18
  21. 2024SAM-E: Leveraging Visual Foundation Model with Sequence Imitation for Embodied Manipulationcited by 18
  22. 2021Orienting Novel 3D Objects Using Self-Supervised Learning of Rotation Transformscited by 17
  23. 2023Deep Fusion Transformer Network with Weighted Vector-Wise Keypoints Voting for Robust 6D Object Pose Estimationcited by 16
  24. 2022Transformers are Adaptable Task Plannerscited by 15
  25. 2021Simultaneous Semantic and Collision Learning for 6-DoF Grasp Pose Estimationcited by 14
  26. 2022Imitation Learning for Nonprehensile Manipulation through Self-Supervised Learning Considering Motion Speedcited by 14
  27. 2024GS-Pose: Generalizable Segmentation-based 6D Object Pose Estimation with 3D Gaussian Splattingcited by 14
  28. 2024LaPose: Laplacian Mixture Shape Modeling for RGB-Based Category-Level Object Pose Estimationcited by 13
  29. 2022Certifiable 3D Object Pose Estimation: Foundations, Learning Models, and Self-Trainingcited by 12
  30. 2023Self-Supervised Unseen Object Instance Segmentation via Long-Term Robot Interactioncited by 10
  31. 2023MFOS: Model-Free & One-Shot Object Pose Estimationcited by 10
  32. 20246DOPE-GS: Online 6D Object Pose Estimation using Gaussian Splattingcited by 10
  33. 2021Learning Visual Shape Control of Novel 3D Deformable Objects from Partial-View Point Cloudscited by 9
  34. 2021IFR-Explore: Learning Inter-object Functional Relationships in 3D Indoor Scenescited by 9
  35. 2022Mobile Robot Manipulation using Pure Object Detectioncited by 8
  36. 2023Uncertainty-aware 3D Object-Level Mapping with Deep Shape Priorscited by 8
  37. 2021Differentiable Rendering with Perturbed Optimizerscited by 7
  38. 2021Depth from Camera Motion and Object Detectioncited by 6

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