PhysGaussian: Physics-Integrated 3D Gaussians for Generative Dynamics

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Abstract
We introduce PhysGaussian, a new method that seamlessly integrates physically grounded Newtonian dynamics within 3D Gaussians to achieve high-quality novel motion synthe-sis. Employing a custom Material Point Method (MPM), our approach enriches 3D Gaussian kernels with physically meaningful kinematic deformation and mechanical stress attributes, all evolved in line with continuum mechanics principles. A defining characteristic of our method is the seamless integration between physical simulation and visual rendering: both components utilize the same 3D Gaussian kernels as their discrete representations. This negates the necessity for triangle/tetrahedron meshing, marching cubes, “cage meshes,” or any other geometry embedding, highlighting the principle of “what you see is what you simulate (WS 2 ).” Our method demonstrates exceptional versatility across a wide variety of materials-including elastic entities, plastic metals, non-Newtonian fluids, and granular materials-showcasing its strong capabilities in creating diverse visual content with novel viewpoints and movements. Our project page is at: https://xpandora.github.io/PhysGaussian/
Funding Information
  • NSF (2301040,2008915,2244651,2008564,2153851,2023780)