Agentic Physics-Grounded Video Generation via Memory-Augmented In-Context Reasoning
Physical plausibility is essential for realistic video generation. Existing methods impose physical guidance before synthesis via simulations or refined prompts, but this can limit dynamic diversity, miss errors that emerge only after generation, and require repeated regeneration when inconsistencies remain. We therefore study a generate-diagnose-repair paradigm that preserves the original generation capability and selectively repairs physical inconsistencies afterward, raising two key questions: what to repair and how to repair? To address them, we introduce PhysRepair, an agentic video generation framework that combines causal reasoning over the observed physical failure with prior repa...
| Authors | Xikang Guan, Shaocong Yang, Yanqi Bao et al. |
|---|---|
| Primary category | cs.CV |
| Published | 16 October 2026 |
| Last updated at source | 16 October 2026 |
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