Phase-aware video generation for physics-grounded dynamics and interactions

2026-10-08

AI Summary

This study addresses the significant challenge of preserving phase-specific motion characteristics while modeling physically consistent interactions in solid-gas coupled dynamics video generation. To this end, we construct a large-scale trajectory corpus comprising 700,000 samples and propose a phase-aware dual-branch architecture that explicitly disentangles and collaboratively models the distinct dynamics of solid and gas phases. Furthermore, a spatiotemporal cross-attention mechanism is designed to precisely capture cross-phase physical coupling relationships. Extensive evaluations demonstrate that our approach significantly outperforms existing methods in terms of motion adherence, physical plausibility, and visual quality, thereby achieving high-fidelity, physics-compliant generation of solid-gas interaction videos.

Abstract

Generating physically plausible videos for solid-gas dynamics is challenging as different phases exhibit distinct dynamics yet remain coupled through physical interactions. We present PAVG, a Phase-Aware Video Generator for solid-gas dynamics and interactions. It employs a dual-branch architecture to explicitly model the distinct dynamics of solids and gases, while spatiotemporal cross-attention captures their physical interactions. This design enables PAVG to preserve phasespecific motion characteristics while producing physically consistent responses across phases. To facilitate this task, we further construct a simulation corpus comprising over 700K physical trajectories across diverse solid, gas, and solid-gas interaction scenarios. Extensive evaluations demonstrate that our PAVG produces videos with improved motion adherence, physical plausibility, and visual quality compared with existing approaches.

Problem

• video generation
• solid-gas dynamics
• physics-grounded
• phase-aware
• physical interactions

Innovation

• Phase-aware video generation
• Solid-gas dynamics
• Dual-branch architecture
• Spatiotemporal cross-attention
• Physics-grounded simulation