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# Material Point Method

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  1. arXiv

    Same object, new material prompt: PhysForge fits physics on contact and deformation windows

    PhysForge treats material-conditioned dynamics from a video diffusion model as references for fitting the physical parameters of 3D assets, so a user-specified material actually changes how an object contacts and deforms. Previously such parameters were largely inferred from appearance, making it hard to assign a material to the same object or to estimate properties from complex interactions between objects and semantic parts. On PhysAssets and Google Scanned Objects it reaches the best CLIP and physical controllability scores for both common and uncommon materials, with average physical controllability 4.3 versus 3.8 for the strongest baseline.

  2. arXiv

    DeformSmith: Turning Text or a Single Image into Graspable Deformable Assets via a Physics Harness

    DeformSmith presents a hierarchical agentic framework that, from text or a single image, progressively builds geometry, a physical model, material behavior, and robot interaction, using a shared physics-grounded harness to evaluate and revise candidates through simulation probes and robot pick-and-place feedback; across 39 cases its assets score higher on visual quality and physical plausibility than baselines including PhysGen3D, PhysGM, and PhysX-Omni, while also producing replayable manipulation data.

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