mlsanityData to 7 Oct 2026

Gravity-guided Contact Dynamics Estimation from 3D Human Motions

arXiv 2606.08133 ↗First posted 6 Jun 2026cs.CVcited by 0

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Abstract (arXiv)

Ground contact forces acting on the human body, are crucial for biomechanics studies or sport performance analysis. Prior methods rely on force plates or pressure mats to collect ground contact dynamics, limiting their applicability to carefully controlled settings. A more scalable solution is to estimate the dynamics directly from motion capture data. Recent approaches only roughly estimate the ground contact dynamics from the vertical distance between the body and the ground plane, which cannot capture the complex pressure distribution of all contact points. To this end, we propose GraCE -- Gravity-guided Contact Dynamics Estimation, a novel full-body contact dynamics model for human motions using a realistic influence of body mass distribution and gravity. We use the human's center of gravity to estimate the ground contacts based on its relative distance to the human body. The applied force on each contact is estimated via the product of predicted contact probabilities and the total exterior force computed from the center of mass trajectory. We outperform related work on the GroundLink dataset for ground reaction force estimation, and on the MOYO dataset for detailed contact pressure prediction. The code is published at https://github.com/cuongle1206/GraCE

Key facts. No citing papers in the map yet (data through 7 Oct 2026). Builds on 22 of its 42 references that are in the map. First posted on arXiv 6 Jun 2026.

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References · 22

  1. 2019Expressive Body Capture: 3D Hands, Face, and Body from a Single Imagecited by 1,600
  2. 2019AMASS: Archive of Motion Capture as Surface Shapescited by 1,208
  3. 2022PhysDiff: Physics-Guided Human Motion Diffusion Modelcited by 365
  4. 2021HuMoR: 3D Human Motion Model for Robust Pose Estimationcited by 319
  5. 2021SimPoE: Simulated Character Control for 3D Human Pose Estimationcited by 111
  6. 20233D Human Pose Estimation via Intuitive Physicscited by 100
  7. 2020Contact and Human Dynamics from Monocular Videocited by 94
  8. 2021Neural Monocular 3D Human Motion Capture with Physical Awarenesscited by 70
  9. 2021Physics-based Human Motion Estimation and Synthesis from Videoscited by 65
  10. 2022D&D: Learning Human Dynamics from Dynamic Cameracited by 39
  11. 2022Differentiable Dynamics for Articulated 3d Human Motion Reconstructioncited by 38
  12. 2022Trajectory Optimization for Physics-Based Reconstruction of 3d Human Pose from Monocular Videocited by 37
10 more
  1. 2022Neural MoCon: Neural Motion Control for Physically Plausible Human Motion Capturecited by 31
  2. 2024PhysPT: Physics-aware Pretrained Transformer for Estimating Human Dynamics from Monocular Videoscited by 27
  3. 2022UnderPressure: Deep Learning for Foot Contact Detection, Ground Reaction Force Estimation and Footskate Cleanupcited by 15
  4. 2023GroundLink: A Dataset Unifying Human Body Movement and Ground Reaction Dynamicscited by 13
  5. 2024AddBiomechanics Dataset: Capturing the Physics of Human Motion at Scalecited by 11
  6. 2024ImDy: Human Inverse Dynamics from Imitated Observationscited by 9
  7. 2024Optimal-state Dynamics Estimation for Physics-based Human Motion Capture from Videoscited by 6
  8. 2022Image-based Stability Quantificationcited by 2
  9. 2025Physics-informed Ground Reaction Dynamics from Human Motion Capturecited by 1
  10. 2025FootFormer: Estimating Stability from Visual Inputcited by 1

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