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ContactPose: A Dataset of Grasps with Object Contact and Hand Pose

arXiv 2007.09545 ↗First posted 19 Jul 2020cs.CVcited by 180

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Abstract (arXiv)

Grasping is natural for humans. However, it involves complex hand configurations and soft tissue deformation that can result in complicated regions of contact between the hand and the object. Understanding and modeling this contact can potentially improve hand models, AR/VR experiences, and robotic grasping. Yet, we currently lack datasets of hand-object contact paired with other data modalities, which is crucial for developing and evaluating contact modeling techniques. We introduce ContactPose, the first dataset of hand-object contact paired with hand pose, object pose, and RGB-D images. ContactPose has 2306 unique grasps of 25 household objects grasped with 2 functional intents by 50 participants, and more than 2.9 M RGB-D grasp images. Analysis of ContactPose data reveals interesting relationships between hand pose and contact. We use this data to rigorously evaluate various data representations, heuristics from the literature, and learning methods for contact modeling. Data, code, and trained models are available at https://contactpose.cc.gatech.edu.

Key facts. Cited by 180 papers in the map (data through 7 Oct 2026). First posted on arXiv 19 Jul 2020.

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Citing papers per year: 2021: 15; 2022: 28; 2023: 38; 2024: 43; 2025: 28; 2026: 28.

180 papers.

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  1. 2022HOI4D: A 4D Egocentric Dataset for Category-Level Human-Object Interactioncited by 321
  2. 2021DexYCB: A Benchmark for Capturing Hand Grasping of Objectscited by 320
  3. 2022ARCTIC: A Dataset for Dexterous Bimanual Hand-Object Manipulationcited by 306
  4. 2021H2O: Two Hands Manipulating Objects for First Person Interaction Recognitioncited by 251
  5. 2022BEHAVE: Dataset and Method for Tracking Human Object Interactionscited by 246
  6. 2021DexMV: Imitation Learning for Dexterous Manipulation from Human Videoscited by 194
  7. 2021Hand-Object Contact Consistency Reasoning for Human Grasps Generationcited by 160
  8. 2021ContactOpt: Optimizing Contact to Improve Graspscited by 137
  9. 2022OakInk: A Large-scale Knowledge Repository for Understanding Hand-Object Interactioncited by 129
  10. 2022DexGraspNet: A Large-Scale Robotic Dexterous Grasp Dataset for General Objects Based on Simulationcited by 129
  11. 2021Keypoint Transformer: Solving Joint Identification in Challenging Hands and Object Interactions for Accurate 3D Pose Estimationcited by 122
  12. 2024HOT3D: Hand and Object Tracking in 3D from Egocentric Multi-View Videoscited by 122
38 more
  1. 2022IMos: Intent-Driven Full-Body Motion Synthesis for Human-Object Interactionscited by 121
  2. 2023Affordance Diffusion: Synthesizing Hand-Object Interactionscited by 110
  3. 2021D-Grasp: Physically Plausible Dynamic Grasp Synthesis for Hand-Object Interactionscited by 109
  4. 2022CHORE: Contact, Human and Object REconstruction from a single RGB imagecited by 95
  5. 2022What's in your hands? 3D Reconstruction of Generic Objects in Handscited by 90
  6. 2022InterCap: Joint Markerless 3D Tracking of Humans and Objects in Interactioncited by 90
  7. 2024TACO: Benchmarking Generalizable Bimanual Tool-ACtion-Object Understandingcited by 85
  8. 2022DexVIP: Learning Dexterous Grasping with Human Hand Pose Priors from Videocited by 83
  9. 2022Fine-Grained Egocentric Hand-Object Segmentation: Dataset, Model, and Applicationscited by 78
  10. 2024OAKINK2: A Dataset of Bimanual Hands-Object Manipulation in Complex Task Completioncited by 78
  11. 2021ArtiBoost: Boosting Articulated 3D Hand-Object Pose Estimation via Online Exploration and Synthesiscited by 76
  12. 2023Diffusion-Guided Reconstruction of Everyday Hand-Object Interaction Clipscited by 73
  13. 2022TOCH: Spatio-Temporal Object-to-Hand Correspondence for Motion Refinementcited by 69
  14. 2024DiffH2O: Diffusion-Based Synthesis of Hand-Object Interactions from Textual Descriptionscited by 60
  15. 2023Visibility Aware Human-Object Interaction Tracking from Single RGB Cameracited by 58
  16. 2021Towards unconstrained joint hand-object reconstruction from RGB videoscited by 57
  17. 2025ManipTrans: Efficient Dexterous Bimanual Manipulation Transfer via Residual Learningcited by 56
  18. 2022GenDexGrasp: Generalizable Dexterous Graspingcited by 54
  19. 2023DECO: Dense Estimation of 3D Human-Scene Contact In The Wildcited by 54
  20. 2024ParaHome: Parameterizing Everyday Home Activities Towards 3D Generative Modeling of Human-Object Interactionscited by 54
  21. 2023ArtiGrasp: Physically Plausible Synthesis of Bi-Manual Dexterous Grasping and Articulationcited by 53
  22. 2023ContactGen: Generative Contact Modeling for Grasp Generationcited by 52
  23. 2021A Skeleton-Driven Neural Occupancy Representation for Articulated Handscited by 50
  24. 2025PyG 2.0: Scalable Learning on Real World Graphscited by 49
  25. 2023AffordPose: A Large-scale Dataset of Hand-Object Interactions with Affordance-driven Hand Posecited by 47
  26. 2022FLEX: Full-Body Grasping Without Full-Body Graspscited by 46
  27. 2024Introducing HOT3D: An Egocentric Dataset for 3D Hand and Object Trackingcited by 46
  28. 2024G-HOP: Generative Hand-Object Prior for Interaction Reconstruction and Grasp Synthesiscited by 43
  29. 2023Detecting Human-Object Contact in Imagescited by 41
  30. 2023Template Free Reconstruction of Human-object Interaction with Procedural Interaction Generationcited by 37
  31. 2024HOIDiffusion: Generating Realistic 3D Hand-Object Interaction Datacited by 37
  32. 2023Object pop-up: Can we infer 3D objects and their poses from human interactions alone?cited by 36
  33. 2022Reconstructing Hand-Held Objects from Monocular Videocited by 35
  34. 2023A Dataset of Relighted 3D Interacting Handscited by 35
  35. 2023Learning Human-to-Robot Handovers from Point Cloudscited by 34
  36. 2024HIMO: A New Benchmark for Full-Body Human Interacting with Multiple Objectscited by 34
  37. 2024EasyHOI: Unleashing the Power of Large Models for Reconstructing Hand-Object Interactions in the Wildcited by 33
  38. 2024Beyond the Contact: Discovering Comprehensive Affordance for 3D Objects from Pre-trained 2D Diffusion Modelscited by 32

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