PhysHanDI: Physics-Based Reconstruction of Hand-Deformable Object Interactions
Not on the map. Why?
Abstract (arXiv)
While existing methods for reconstructing hand-object interactions have made impressive progress, they either focus on rigid or part-wise rigid objects-limiting their ability to model real-world objects (e.g., cloth, stuffed animals) that exhibit highly non-rigid deformations-or model deformable objects without full 3D hand reconstruction. To bridge this gap, we present PhysHanDI (Physics-based Reconstruction of Hand and Deformable Object Interactions), a framework that enables full 3D reconstruction of both interacting hands and non-rigid objects. Our key idea is to physically simulate object deformations driven by forces induced from densely reconstructed 3D hand motions, ensuring that the reconstructed object dynamics are both physically plausible and coherent with the interacting hand movements. Furthermore, we demonstrate that such simulation of object deformations can, in turn, refine and improve hand reconstruction via inverse physics. In experiments, PhysHanDI outperforms the state-of-the-art baseline across reconstruction and future prediction.
Key facts. No citing papers in the map yet (data through 7 Oct 2026). Builds on 58 of its 82 references that are in the map. First posted on arXiv 10 May 2026.
Builds on
58 of 82 references.
References · 58
- 2018Occupancy Networks: Learning 3D Reconstruction in Function Spacecited by 2,037
- 2020D-NeRF: Neural Radiance Fields for Dynamic Scenescited by 1,459
- 2024Structured 3D Latents for Scalable and Versatile 3D Generationcited by 742
- 2023Dynamic 3D Gaussians: Tracking by Persistent Dynamic View Synthesiscited by 731
- 2020Rescaling Egocentric Visioncited by 529
- 2020Non-Rigid Neural Radiance Fields: Reconstruction and Novel View Synthesis of a Dynamic Scene From Monocular Videocited by 470
- 2020Space-time Neural Irradiance Fields for Free-Viewpoint Videocited by 414
- 2020GRAB: A Dataset of Whole-Body Human Grasping of Objectscited by 397
- 2019Learning joint reconstruction of hands and manipulated objectscited by 377
- 2021DexYCB: A Benchmark for Capturing Hand Grasping of Objectscited by 320
- 2022ARCTIC: A Dataset for Dexterous Bimanual Hand-Object Manipulationcited by 306
- 2020HybrIK: A Hybrid Analytical-Neural Inverse Kinematics Solution for 3D Human Pose and Shape Estimationcited by 304
38 more
- 2017First-Person Hand Action Benchmark with RGB-D Videos and 3D Hand Pose Annotationscited by 229
- 2022DynIBaR: Neural Dynamic Image-Based Renderingcited by 224
- 2024PhysDreamer: Physics-Based Interaction with 3D Objects via Video Generationcited by 185
- 2020ContactPose: A Dataset of Grasps with Object Contact and Hand Posecited by 180
- 2023HyperReel: High-Fidelity 6-DoF Video with Ray-Conditioned Samplingcited by 173
- 2019ContactDB: Analyzing and Predicting Grasp Contact via Thermal Imagingcited by 145
- 2023PAC-NeRF: Physics Augmented Continuum Neural Radiance Fields for Geometry-Agnostic System Identificationcited by 145
- 2021Semi-Supervised 3D Hand-Object Poses Estimation with Interactions in Timecited by 140
- 2019H+O: Unified Egocentric Recognition of 3D Hand-Object Poses and Interactionscited by 139
- 2020Leveraging Photometric Consistency over Time for Sparsely Supervised Hand-Object Reconstructioncited by 139
- 2021ContactOpt: Optimizing Contact to Improve Graspscited by 137
- 2023DynMF: Neural Motion Factorization for Real-time Dynamic View Synthesis with 3D Gaussian Splattingcited by 124
- 2021Keypoint Transformer: Solving Joint Identification in Challenging Hands and Object Interactions for Accurate 3D Pose Estimationcited by 122
- 2020HOPE-Net: A Graph-based Model for Hand-Object Pose Estimationcited by 112
- 2021gradSim: Differentiable simulation for system identification and visuomotor controlcited by 100
- 2024Reconstruction and Simulation of Elastic Objects with Spring-Mass 3D Gaussianscited by 92
- 2017Real-time Hand Tracking under Occlusion from an Egocentric RGB-D Sensorcited by 84
- 2025PhysTwin: Physics-Informed Reconstruction and Simulation of Deformable Objects from Videoscited by 78
- 2021DiffPD: Differentiable Projective Dynamicscited by 62
- 2022AlignSDF: Pose-Aligned Signed Distance Fields for Hand-Object Reconstructioncited by 58
- 2022Physics Informed Neural Fields for Smoke Reconstruction with Sparse Datacited by 52
- 2023ContactGen: Generative Contact Modeling for Grasp Generationcited by 52
- 2022NeuPhysics: Editable Neural Geometry and Physics from Monocular Videoscited by 50
- 2023gSDF: Geometry-Driven Signed Distance Functions for 3D Hand-Object Reconstructioncited by 49
- 2024Hamba: Single-view 3D Hand Reconstruction with Graph-guided Bi-Scanning Mambacited by 45
- 2023Flow supervision for Deformable NeRFcited by 42
- 2024Dynamic 3D Gaussian Tracking for Graph-Based Neural Dynamics Modelingcited by 42
- 2020Joint Hand-object 3D Reconstruction from a Single Image with Cross-branch Feature Fusioncited by 39
- 2022Differentiable Simulation of Soft Multi-body Systemscited by 39
- 2020Physics-Based Dexterous Manipulations with Estimated Hand Poses and Residual Reinforcement Learningcited by 37
- 2022Virtual Elastic Objectscited by 35
- 2024BimArt: A Unified Approach for the Synthesis of 3D Bimanual Interaction with Articulated Objectscited by 29
- 2024InterHandGen: Two-Hand Interaction Generation via Cascaded Reverse Diffusioncited by 28
- 2023Im2Hands: Learning Attentive Implicit Representation of Interacting Two-Hand Shapescited by 26
- 2023ContactArt: Learning 3D Interaction Priors for Category-level Articulated Object and Hand Poses Estimationcited by 16
- 2023SHOWMe: Benchmarking Object-agnostic Hand-Object 3D Reconstructioncited by 16
- 2024Dense Hand-Object(HO) GraspNet with Full Grasping Taxonomy and Dynamicscited by 15
- 2023HMDO: Markerless Multi-view Hand Manipulation Capture with Deformable Objectscited by 12
50 most cited of 58 All 58 (JSON)
Built on by
Not cited yet.