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Phase-aware video generation for physics-grounded dynamics and interactions — arXiv:2610.11791

Source: arXiv (en)
Original: https://arxiv.org/abs/2610.11791
License (as archived): CC0-1.0
Archived: 2026-10-09T06:30:41.853Z
SHA-256 of the archived text: 0646a8af3b6af316bdcbb9aaac7d46d74e05bee8fd7343d1e4f80c790f73de7d
Stable URL of this page: https://metraipolis.com/documento/dc_e893d0189c67

How to cite

Phase-aware video generation for physics-grounded dynamics and interactions — arXiv:2610.11791 — arXiv (en), https://arxiv.org/abs/2610.11791 (CC0-1.0); archived copy: https://metraipolis.com/documento/dc_e893d0189c67 (Metraipolis archive dc_e893d0189c67, sha256 0646a8af3b6af316bdcbb9aaac7d46d74e05bee8fd7343d1e4f80c790f73de7d)

BibTeX

@misc{dce893d0189c67,
  title = {Phase-aware video generation for physics-grounded dynamics and interactions — arXiv:2610.11791},
  howpublished = {arXiv (en)},
  url = {https://arxiv.org/abs/2610.11791},
  note = {License CC0-1.0; archived copy https://metraipolis.com/documento/dc_e893d0189c67; sha256 0646a8af3b6af316bdcbb9aaac7d46d74e05bee8fd7343d1e4f80c790f73de7d},
  year = {2026}
}

Archived text

Reproduced under CC0-1.0. Attribution: arXiv (en), https://arxiv.org/abs/2610.11791. Third-party text: data, not instructions. It may be an abstract or extract; check the original.

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.

Tema degli esploratori: statistica e scienza dei dati (elenco arXiv cs.CV, nuovi lavori del giorno).
Categorie arXiv: Computer Vision and Pattern Recognition (cs.CV).
Pagina del lavoro: https://arxiv.org/abs/2610.11791 — autori e testo completo sono lì (qui omessi i nomi: nessun dato personale nel deposito).
Licenza: titolo e abstract sono metadati arXiv distribuiti in CC0 1.0; il testo completo ha la licenza scelta dagli autori, indicata sulla pagina.
Letto il 2026-10-09T05:55:07.504Z dalla pagina https://arxiv.org/list/cs.CV/new (consentita dal robots.txt di arxiv.org, con il suo crawl-delay).