14 papers
BoxTwin: Learning Elastoplastic Articulated Object Dynamics from Videos
Heng Zhang, Gehan Zheng, Kaifeng Zhang +6
Digital twins enable robots to anticipate and adapt to physical interactions, but existing models struggle with elastoplastic articulated objects (EAOs) that exhibit nonlinear elas…
Closing Trajectories: Equation-Free Cyclic Animation via Koopman Surrogates
Shixun Huang, Siyuan Chen, Yue Chang +2
Cyclic animation is widely used in computer graphics and interactive content.It supports seamless playback in games, VR, and interactive simulation,where short clips must repeat sm…
MeGAS: Thermomechanical Dynamic Gaussian Splatting for Thermophysical Scene Editing
Zesong Yang, Yuanhang Lei, Liyuan Cui +6
Recent advances integrate physically grounded Newtonian dynamics with neural rendering frameworks, narrowing the gap between photorealistic scene reconstruction and physics-based a…
Low-Rank Koopman Deformables with Log-Linear Time Integration
Yue Chang, Peter Yichen Chen, Eitan Grinspun +1
We present a low-rank Koopman operator formulation for accelerating deformable subspace simulation. Using a Dynamic Mode Decomposition (DMD) parameterization of the Koopman operato…
PINNsur: Physics-Informed Neural Networks for PDEs on Curved Surfaces
Pranav Jain, Navami Kairanda, Peter Yichen Chen +1
Partial differential equations (PDEs) on surfaces are fundamental to scientific computing and geometry processing. A popular approach to solving PDEs on surfaces is the finite elem…
PhysSkin: Real-Time and Generalizable Physics-Based Animation via Self-Supervised Neural Skinning
Yuanhang Lei, Tao Cheng, Xingxuan Li +6
Achieving real-time physics-based animation that generalizes across diverse 3D shapes and discretizations remains a fundamental challenge. We introduce PhysSkin, a physics-informed…