mlsanityData to 7 Oct 2026

AdaAfford: Learning to Adapt Manipulation Affordance for 3D Articulated Objects via Few-shot Interactions

arXiv 2112.00246 ↗First posted 1 Dec 2021cs.CV cs.ROcited by 56

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Abstract (arXiv)

Perceiving and interacting with 3D articulated objects, such as cabinets, doors, and faucets, pose particular challenges for future home-assistant robots performing daily tasks in human environments. Besides parsing the articulated parts and joint parameters, researchers recently advocate learning manipulation affordance over the input shape geometry which is more task-aware and geometrically fine-grained. However, taking only passive observations as inputs, these methods ignore many hidden but important kinematic constraints (e.g., joint location and limits) and dynamic factors (e.g., joint friction and restitution), therefore losing significant accuracy for test cases with such uncertainties. In this paper, we propose a novel framework, named AdaAfford, that learns to perform very few test-time interactions for quickly adapting the affordance priors to more accurate instance-specific posteriors. We conduct large-scale experiments using the PartNet-Mobility dataset and prove that our system performs better than baselines.

Key facts. Cited by 56 papers in the map (data through 7 Oct 2026). Builds on 34 of its 46 references that are in the map. First posted on arXiv 1 Dec 2021.

Builds on

34 of 46 references.

References · 34

  1. 2017Model-Agnostic Meta-Learning for Fast Adaptation of Deep Networkscited by 4,861
  2. 2017PointNet++: Deep Hierarchical Feature Learning on Point Sets in a Metric Spacecited by 4,384
  3. 2020SAPIEN: A SimulAted Part-based Interactive ENvironmentcited by 584
  4. 2018PartNet: A Large-scale Benchmark for Fine-grained and Hierarchical Part-level 3D Object Understandingcited by 521
  5. 2019Efficient Off-Policy Meta-Reinforcement Learning via Probabilistic Context Variablescited by 372
  6. 2021Where2Act: From Pixels to Actions for Articulated 3D Objectscited by 179
  7. 2016Learning to Poke by Poking: Experiential Learning of Intuitive Physicscited by 152
  8. 2017Preparing for the Unknown: Learning a Universal Policy with Online System Identificationcited by 129
  9. 2020CPF: Learning a Contact Potential Field to Model the Hand-Object Interactioncited by 127
  10. 2019Shape2Motion: Joint Analysis of Motion Parts and Attributes from 3D Shapescited by 117
  11. 2013Deep Learning for Detecting Robotic Graspscited by 114
  12. 2021Synergies Between Affordance and Geometry: 6-DoF Grasp Detection via Implicit Representationscited by 107
22 more
  1. 2021CAPTRA: CAtegory-level Pose Tracking for Rigid and Articulated Objects from Point Cloudscited by 83
  2. 2020Learning Dexterous Grasping with Object-Centric Visual Affordancescited by 80
  3. 2021VAT-Mart: Learning Visual Action Trajectory Proposals for Manipulating 3D ARTiculated Objectscited by 78
  4. 2014Real-Time Grasp Detection Using Convolutional Neural Networkscited by 75
  5. 2019Putting Humans in a Scene: Learning Affordance in 3D Indoor Environmentscited by 72
  6. 2019KETO: Learning Keypoint Representations for Tool Manipulationcited by 68
  7. 2018Deep Part Induction from Articulated Object Pairscited by 66
  8. 2020Learning Affordance Landscapes for Interaction Exploration in 3D Environmentscited by 65
  9. 2021UMPNet: Universal Manipulation Policy Network for Articulated Objectscited by 64
  10. 2019DensePhysNet: Learning Dense Physical Object Representations via Multi-step Dynamic Interactionscited by 61
  11. 2018Reasoning About Physical Interactions with Object-Oriented Prediction and Planningcited by 51
  12. 2019S4G: Amodal Single-view Single-Shot SE(3) Grasp Detection in Cluttered Scenescited by 51
  13. 2021O2O-Afford: Annotation-Free Large-Scale Object-Object Affordance Learningcited by 46
  14. 2019Environment Probing Interaction Policiescited by 39
  15. 2019Learning Task-Oriented Grasping from Human Activity Datasetscited by 32
  16. 2019DoorGym: A Scalable Door Opening Environment And Baseline Agentcited by 26
  17. 2020RPM-Net: Recurrent Prediction of Motion and Parts from Point Cloudcited by 26
  18. 2020MELD: Meta-Reinforcement Learning from Images via Latent State Modelscited by 22
  19. 2020Learning to Move with Affordance Mapscited by 15
  20. 2016Reconstructing Articulated Rigged Models from RGB-D Videoscited by 8
  21. 2019Learning Visual Dynamics Models of Rigid Objects using Relational Inductive Biasescited by 2
  22. 2021Few Shot System Identification for Reinforcement Learningcited by 1

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2022: 3; 2023: 13; 2024: 26; 2025: 9; 2026: 5.

56 papers.

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  1. 2024General Flow as Foundation Affordance for Scalable Robot Learningcited by 80
  2. 2024Robo-ABC: Affordance Generalization Beyond Categories via Semantic Correspondence for Robot Manipulationcited by 69
  3. 2023Grounding 3D Object Affordance from 2D Interactions in Imagescited by 62
  4. 2024RAM: Retrieval-Based Affordance Transfer for Generalizable Zero-Shot Robotic Manipulationcited by 55
  5. 2022End-to-End Affordance Learning for Robotic Manipulationcited by 54
  6. 2023LEMON: Learning 3D Human-Object Interaction Relation from 2D Imagescited by 49
  7. 2024RoboEXP: Action-Conditioned Scene Graph via Interactive Exploration for Robotic Manipulationcited by 48
  8. 2025Articulate AnyMesh: Open-Vocabulary 3D Articulated Objects Modelingcited by 41
  9. 2023PartManip: Learning Cross-Category Generalizable Part Manipulation Policy from Point Cloud Observationscited by 40
  10. 2024Deep Generative Models in Robotics: A Survey on Learning from Multimodal Demonstrationscited by 35
  11. 2024A Survey of Embodied Learning for Object-Centric Robotic Manipulationcited by 34
  12. 2023Understanding 3D Object Interaction from a Single Imagecited by 33
38 more
  1. 2023Where2Explore: Few-shot Affordance Learning for Unseen Novel Categories of Articulated Objectscited by 33
  2. 2024ASID: Active Exploration for System Identification in Robotic Manipulationcited by 27
  3. 2024EgoChoir: Capturing 3D Human-Object Interaction Regions from Egocentric Viewscited by 26
  4. 2023Learning Foresightful Dense Visual Affordance for Deformable Object Manipulationcited by 25
  5. 2024GenDP: 3D Semantic Fields for Category-Level Generalizable Diffusion Policycited by 25
  6. 2023Learning Environment-Aware Affordance for 3D Articulated Object Manipulation under Occlusionscited by 23
  7. 2024UniGarmentManip: A Unified Framework for Category-Level Garment Manipulation via Dense Visual Correspondencecited by 22
  8. 20233D Implicit Transporter for Temporally Consistent Keypoint Discoverycited by 20
  9. 2022DualAfford: Learning Collaborative Visual Affordance for Dual-gripper Manipulationcited by 18
  10. 2024ScrewMimic: Bimanual Imitation from Human Videos with Screw Space Projectioncited by 16
  11. 2024Survey on Modeling of Human-made Articulated Objectscited by 14
  12. 2024Open-World Reinforcement Learning over Long Short-Term Imaginationcited by 13
  13. 2025AdaManip: Adaptive Articulated Object Manipulation Environments and Policy Learningcited by 12
  14. 2024PreAfford: Universal Affordance-Based Pre-Grasping for Diverse Objects and Environmentscited by 11
  15. 2024ManiFoundation Model for General-Purpose Robotic Manipulation of Contact Synthesis with Arbitrary Objects and Robotscited by 11
  16. 2025ArticuBot: Learning Universal Articulated Object Manipulation Policy via Large Scale Simulationcited by 10
  17. 2023On the Efficacy of 3D Point Cloud Reinforcement Learningcited by 9
  18. 2024Seeing the Unseen: Visual Common Sense for Semantic Placementcited by 9
  19. 2024Part-Guided 3D RL for Sim2Real Articulated Object Manipulationcited by 9
  20. 2025GarmentPile: Point-Level Visual Affordance Guided Retrieval and Adaptation for Cluttered Garments Manipulationcited by 9
  21. 2025Weakly-Supervised Affordance Grounding Guided by Part-Level Semantic Priorscited by 9
  22. 2024FIction: 4D Future Interaction Prediction from Videocited by 8
  23. 2026SceneCode: Executable World Programs for Editable Indoor Scenes with Articulated Objectscited by 7
  24. 2024EqvAfford: SE(3) Equivariance for Point-Level Affordance Learningcited by 6
  25. 2024ConceptFactory: Facilitate 3D Object Knowledge Annotation with Object Conceptualizationcited by 6
  26. 2023ImageManip: Image-based Robotic Manipulation with Affordance-guided Next View Selectioncited by 5
  27. 2023Interaction-Driven Active 3D Reconstruction with Object Interiorscited by 5
  28. 2023Learning Part Motion of Articulated Objects Using Spatially Continuous Neural Implicit Representationscited by 5
  29. 2023SAGE: Bridging Semantic and Actionable Parts for GEneralizable Manipulation of Articulated Objectscited by 5
  30. 2024MARS: Multimodal Active Robotic Sensing for Articulated Characterizationcited by 5
  31. 2024Discovering Conceptual Knowledge with Analytic Ontology Templates for Articulated Objectscited by 5
  32. 2025Part Segmentation and Motion Estimation for Articulated Objects with Dynamic 3D Gaussianscited by 5
  33. 2024DISCO: Embodied Navigation and Interaction via Differentiable Scene Semantics and Dual-level Controlcited by 4
  34. 2024GAPartManip: A Large-scale Part-centric Dataset for Material-Agnostic Articulated Object Manipulationcited by 4
  35. 2022H-SAUR: Hypothesize, Simulate, Act, Update, and Repeat for Understanding Object Articulations from Interactionscited by 3
  36. 2025BiAssemble: Learning Collaborative Affordance for Bimanual Geometric Assemblycited by 3
  37. 2026A3D: Adaptive Affordance Assembly with Dual-Arm Manipulationcited by 3
  38. 2026Learning Part-Aware Dense 3D Feature Field for Generalizable Articulated Object Manipulationcited by 3

50 most cited of 56 All 56 (JSON)