English

Half-Physics: Enabling Kinematic 3D Human Model with Physical Interactions

Computer Vision and Pattern Recognition 2025-08-13 v2

Abstract

While current general-purpose 3D human models (e.g., SMPL-X) efficiently represent accurate human shape and pose, they lacks the ability to physically interact with the environment due to the kinematic nature. As a result, kinematic-based interaction models often suffer from issues such as interpenetration and unrealistic object dynamics. To address this limitation, we introduce a novel approach that embeds SMPL-X into a tangible entity capable of dynamic physical interactions with its surroundings. Specifically, we propose a "half-physics" mechanism that transforms 3D kinematic motion into a physics simulation. Our approach maintains kinematic control over inherent SMPL-X poses while ensuring physically plausible interactions with scenes and objects, effectively eliminating penetration and unrealistic object dynamics. Unlike reinforcement learning-based methods, which demand extensive and complex training, our half-physics method is learning-free and generalizes to any body shape and motion; meanwhile, it operates in real time. Moreover, it preserves the fidelity of the original kinematic motion while seamlessly integrating physical interactions

Keywords

Cite

@article{arxiv.2507.23778,
  title  = {Half-Physics: Enabling Kinematic 3D Human Model with Physical Interactions},
  author = {Li Siyao and Yao Feng and Omid Taheri and Chen Change Loy and Michael J. Black},
  journal= {arXiv preprint arXiv:2507.23778},
  year   = {2025}
}
R2 v1 2026-07-01T04:28:17.286Z