Phys4DRT: Physics-based 4D Generation for Real-Time Interaction with Time-Frequency Supervision

Generating highly realistic 4D interaction in real time is significant for visual content generation. Although existing works have validated to produce impressive dynamics by employing physical simulation and learned material mainly from pre-trained video diffusion models, it is still challenging to generate real-time 4D interaction with high-quality motion due to the heavy time consumption of the simulation solver and indirect material learning strategy. This paper proposes a novel physics-based 4D generation method, Phys4DRT, for arbitrary realistic real-time interaction on 3D Gaussian Splatting (3DGS) objects with direct motion supervision in time-frequency domain. Specifically, we devise a fast and differentiable eXtended Position Based Dynamics (XPBD) simulator as the light-weight controller for efficient physical evolution on a quasi-regular tetrahedral proxy mesh, into which we immerse the static 3DGS for efficient and stable deformation simulation. In addition, to learn the heterogeneous material for realistic motion, we directly supervise the generated dynamic 3D behavior by the motion representation of the optical flow and spectral volume extracted from the generated reference video, rather than indirect supervision in the color space used in previous approaches. We thoroughly conduct experiments on the public benchmarks to demonstrate the efficiency and effectiveness of our method. Our model can accelerate real-time 4D interaction generation by approximately x20 faster than the current Material Point Method (MPM) based approaches while achieving competitive visual quality compared with the state-of-the-art baselines.