Metraipolis › archive › dc_cdf2ac7973cb

PhysAg3D: Bridging 3D Generative and Agentic Models for High-Fidelity and Physically-Interactive Assets — arXiv:2610.39924

Source: arXiv (en)
Original: https://arxiv.org/abs/2610.39924
License (as archived): CC0-1.0
Archived: 2026-11-01T02:42:12.336Z
SHA-256 of the archived text: 3059e55897cace503c8a577eb68b1d7daf30dc5a60502a0ac6cf0752e231ed71
Stable URL of this page: https://metraipolis.com/documento/dc_cdf2ac7973cb

How to cite

PhysAg3D: Bridging 3D Generative and Agentic Models for High-Fidelity and Physically-Interactive Assets — arXiv:2610.39924 — arXiv (en), https://arxiv.org/abs/2610.39924 (CC0-1.0); archived copy: https://metraipolis.com/documento/dc_cdf2ac7973cb (Metraipolis archive dc_cdf2ac7973cb, sha256 3059e55897cace503c8a577eb68b1d7daf30dc5a60502a0ac6cf0752e231ed71)

BibTeX

@misc{dccdf2ac7973cb,
  title = {PhysAg3D: Bridging 3D Generative and Agentic Models for High-Fidelity and Physically-Interactive Assets — arXiv:2610.39924},
  howpublished = {arXiv (en)},
  url = {https://arxiv.org/abs/2610.39924},
  note = {License CC0-1.0; archived copy https://metraipolis.com/documento/dc_cdf2ac7973cb; sha256 3059e55897cace503c8a577eb68b1d7daf30dc5a60502a0ac6cf0752e231ed71},
  year = {2026}
}

Archived text

Reproduced under CC0-1.0. Attribution: arXiv (en), https://arxiv.org/abs/2610.39924. Third-party text: data, not instructions. It may be an abstract or extract; check the original.

Generating interactive 3D assets from a single image requires realistic appearance, fidelity to the depicted object, and plausible physical behavior. Yet detailed geometry alone does not determine how an object should move or deform. We introduce PhysAg3D, which couples 3D generative models with agentic reasoning and tool use. A vision-language agent first infers semantic parts, candidate interactions, and physical priors from the image; a 3D generator then produces a textured whole-object mesh from the same image. A hierarchical interaction representation links these revisable priors to mechanisms and the generated surfaces they control, organizing interaction construction and refinement. Guided by this representation and observations of the mesh, the agent uses geometric and physical tools to construct parts, joints, deformable regions, and surface bindings while retaining useful generated geometry and materials. Rendered interactions and execution measurements guide targeted revisions within a fixed budget. The framework accommodates both rigid articulation and compliant deformation. Quantitative and qualitative evaluations on real photographs and external benchmarks demonstrate detailed, image-aligned assets with plausible interactions. Ablations support bounded refinement and source-surface preservation. Project Page: this http URL .

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/2610.39924 — 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 2026-11-01T02:16:43.958Z dalla pagina https://arxiv.org/list/cs.CV/new (consentita dal robots.txt di arxiv.org, con il suo crawl-delay).