arXiv 2610.26067 · cs.CV · 2026-10-19
PhysSkin++: Real-Time and Generalizable Physics-Based Animation via Self-Supervised Neural Skinning
Yuanhang Lei, Baofei Liu, Xingxuan Li, Tao Cheng, Zixuan Wang, Boming Zhao, Yujun Shen, Siyuan Huang 等 12 人
zju3dv
在最新榜 #282 本站收录于 2026-10-24
一句话要点
浙大 3D 视觉组的 PhysSkin++ 从静态几何学习连续神经蒙皮场，构造紧凑的形变子空间，实现跨形状、跨离散方式的实时物理动画；不需逐物体训练，也不需仿真轨迹，用物理约束的自监督学习训练。
ZJU's PhysSkin++ learns continuous neural skinning fields from static geometry to build compact deformation subspaces for real-time physics-based animation that generalizes across shapes and discretizations — no per-object training and no simulation trajectories, via physics-informed self-supervised learning.
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数据说明
元数据来自 arXiv API（已核实）；点赞来自 Hugging Face 每日论文；引用来自 Semantic Scholar。最近刷新 2026-10-26。
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