PhysRig is a differentiable, physics-based skinning and rigging framework that enables realistic deformation of articulated 3D objects. Unlike traditional methods like Linear Blend Skinning (LBS), PhysRig embeds skeletons into a deformable soft-body volume simulated using Material Point Method (MPM) — capturing the behavior of soft tissues, tails, ears, and other elastic structures in a physically plausible way.
🔧 From UIUC & Stability AI | 🦖 ICCV 2025 Accepted
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Differentiable Physics-Based Simulation
Deformations are modeled using MPM and continuum mechanics, supporting gradient-based optimization of both motion and material properties. -
Material Prototypes
Learnable elastic parameter templates (Young’s modulus & Poisson’s ratio) provide expressive yet compact material modeling. -
Driving Point Rigging
Instead of bone transformations, PhysRig uses velocity-driven embedded points to induce dynamic shape changes. -
Strong Performance
Outperforms LBS on both user studies and geometric metrics (Chamfer Distance), with better convergence and physical realism. -
Applications
- Inverse Skinning (from motion to parameters)
- Pose Transfer (e.g., human → jellyfish)
- 4D Reconstruction & Animation