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Fysiverse-3D-SimReady Technical Report: Agentic Physical Simulation for Pragmatic 3D World Reconstruction — arXiv:2609.31715

Source: arXiv (en)
Original: https://arxiv.org/abs/2609.31715
License (as archived): CC0-1.0
Archived: 2026-10-07T23:50:30.307Z
SHA-256 of the archived text: 38a80ac1b50984a6a265e398ebe480d4a5fa0f150ef14fec5da465c7622403d0
Stable URL of this page: https://metraipolis.com/documento/dc_47bcc962002e

How to cite

Fysiverse-3D-SimReady Technical Report: Agentic Physical Simulation for Pragmatic 3D World Reconstruction — arXiv:2609.31715 — arXiv (en), https://arxiv.org/abs/2609.31715 (CC0-1.0); archived copy: https://metraipolis.com/documento/dc_47bcc962002e (Metraipolis archive dc_47bcc962002e, sha256 38a80ac1b50984a6a265e398ebe480d4a5fa0f150ef14fec5da465c7622403d0)

BibTeX

@misc{dc47bcc962002e,
  title = {Fysiverse-3D-SimReady Technical Report: Agentic Physical Simulation for Pragmatic 3D World Reconstruction — arXiv:2609.31715},
  howpublished = {arXiv (en)},
  url = {https://arxiv.org/abs/2609.31715},
  note = {License CC0-1.0; archived copy https://metraipolis.com/documento/dc_47bcc962002e; sha256 38a80ac1b50984a6a265e398ebe480d4a5fa0f150ef14fec5da465c7622403d0},
  year = {2026}
}

Archived text

Reproduced under CC0-1.0. Attribution: arXiv (en), https://arxiv.org/abs/2609.31715. Third-party text: data, not instructions. It may be an abstract or extract; check the original.

Agentic recognition requires visual perception to move beyond static scene understanding and produce structured scene representations that support the perception--reasoning--action loop. Existing single-image 3D generation methods, however, mainly produce visually plausible object assets rather than simulation-ready scene states. When independently generated meshes are composed in a shared space, they may fail to align with the input camera, violate gravity, interpenetrate nearby objects, or become unstable under physics simulation. We present Fysiverse-3D-SimReady, a grounded refinement framework for reconstructing simulation-ready multi-object scenes from a single RGB image with instance and ground prompts. The method places generated object meshes into a shared gravity-aligned scene, refines their camera-space poses through differentiable rendering, and corrects scene-level supports and contacts for stable physical execution. The scene is then used by an agentic simulation workflow, which converts a scene-specific task goal into an executable physics rollout rendered from the original camera view. Experiments show that Fysiverse-3D-SimReady improves input-view alignment, contact plausibility, and physical stability over existing single-image reconstruction and scene generation baselines, while enabling goal-conditioned physical interactions from a single image.

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/2609.31715 — 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 2026-10-07T23:29:26.890Z 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).