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VideoPhysEdit: Physical Counterfactual Video Editing via Rigid-Body Physical Scene Reconstruction — arXiv:2609.35134

Source: arXiv (en)
Original: https://arxiv.org/abs/2609.35134
License (as archived): CC0-1.0
Archived: 2026-10-07T23:52:42.218Z
SHA-256 of the archived text: e77c86532f65c8b93b1a974cee1e84c1eb1f23ac75fa4b6d6f9f060c16b58f70
Stable URL of this page: https://metraipolis.com/documento/dc_5f388ded72cd

How to cite

VideoPhysEdit: Physical Counterfactual Video Editing via Rigid-Body Physical Scene Reconstruction — arXiv:2609.35134 — arXiv (en), https://arxiv.org/abs/2609.35134 (CC0-1.0); archived copy: https://metraipolis.com/documento/dc_5f388ded72cd (Metraipolis archive dc_5f388ded72cd, sha256 e77c86532f65c8b93b1a974cee1e84c1eb1f23ac75fa4b6d6f9f060c16b58f70)

BibTeX

@misc{dc5f388ded72cd,
  title = {VideoPhysEdit: Physical Counterfactual Video Editing via Rigid-Body Physical Scene Reconstruction — arXiv:2609.35134},
  howpublished = {arXiv (en)},
  url = {https://arxiv.org/abs/2609.35134},
  note = {License CC0-1.0; archived copy https://metraipolis.com/documento/dc_5f388ded72cd; sha256 e77c86532f65c8b93b1a974cee1e84c1eb1f23ac75fa4b6d6f9f060c16b58f70},
  year = {2026}
}

Archived text

Reproduced under CC0-1.0. Attribution: arXiv (en), https://arxiv.org/abs/2609.35134. Third-party text: data, not instructions. It may be an abstract or extract; check the original.

Video editing has advanced substantially in recent years, with methods increasingly accounting for the visual consequences of edits, such as changes to shadows and occlusions. However, the physical consequences of edits, including changes to subsequent motion and interactions, remain less explored. We formulate this problem as physical counterfactual video editing (PCVE), which aims to generate a counterfactual video depicting the resulting motion and interactions given a source video, a physical edit, and its execution frame. PCVE is challenging because it requires understanding scene physics and inferring the downstream motion and interactions induced by a physical intervention, while paired factual and counterfactual data and dedicated evaluation metrics are lacking. We introduce VideoPhysEdit, a new training-free pipeline for PCVE in rigid-body scenes. It makes physical reasoning explicit through a novel physical scene reconstruction method that recovers a scene reproducing the observed motion and interactions under simulation, enabling the pipeline to apply physical edits as interventions and use the resulting trajectories to guide counterfactual video generation. We further construct PCVE-RigidBench, a synthetic benchmark with paired source and counterfactual target videos and physical ground truth, and introduce the Physical Edit Score. VideoPhysEdit achieves substantially higher physical edit accuracy than open-source methods and commercial models while maintaining competitive visual fidelity. Its Physical Edit Score is 0.376, the only positive score among the compared methods. Qualitative comparisons on real videos further show that VideoPhysEdit applies to real-world scenes and better depicts the downstream motion and interactions induced by the edits than the compared methods. Code: this https URL

Tema degli esploratori: statistica e scienza dei dati (retro-catalogo arXiv: annunci del 2026-09-29 in cs.CV).
Categorie arXiv: Computer Vision and Pattern Recognition (cs.CV).
Pagina del lavoro: https://arxiv.org/abs/2609.35134 — 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 2026-10-07T23:29:27.532Z dalla pagina https://arxiv.org/catchup/cs.CV/2026-09-29?abs=True (consentita dal robots.txt di arxiv.org, con il suo crawl-delay).