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arXiv Computer Vision By Tahira Kazimi, Shubhankar Borse, Munawar Hayat, Fatih Porikli, Pinar Yanardag

HiPhy: Hierarchical Alignment for Physically-Plausible Multi-Principle Video Generation

Read the original on arXiv Computer Vision →

HiPhy introduces a hierarchical reinforcement learning framework for video generation that enforces physical laws at both local and global levels. It addresses the challenge of multi-principle interactions—such as buoyancy and fluid dynamics occurring simultaneously—by ensuring each principle’s temporal dynamics and the overall scene’s coherence. The authors also provide a 50K-prompt dataset and the MultiPhyBench benchmark, demonstrating that HiPhy outperforms existing methods, especially in scenes with multiple concurrent physical principles.

Machine-generated by The Flow from the publisher's headline and feed description — not written or checked by a human. The full article lives at arXiv Computer Vision.

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