mlsanityData to 14 Oct 2026

PhysForge: Material-Controllable 3D Reconstruction with Separable Components

arXiv 2610.13681 ↗First posted 9 Oct 2026cs.CVcited by 0

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Abstract (arXiv)

Recent advances in physical 3D generation have enabled visually faithful assets with simulatable mechanical behavior. However, existing methods provide limited control over material behavior beyond appearance-based inference and struggle to estimate physical properties from complex interactions between objects and semantic parts. Therefore, we present PhysForge, a Video Diffusion Model (VDM)-based framework for addressing these challenges, comprising two complementary modules for material-controllable physical fitting and componentlevel interaction modeling. The first, PhysFit, leverages material-conditioned VDM dynamics as references for physical-property fitting, introducing windowed fitting to focus on material-revealing interactions and Hallucinated Forcing to disentangle nonphysical motion hallucinated by the VDM from material responses. The second, PhysComp decomposes complex interactions into individual objects and semantic components, enabling their physical parameters to be optimized independently and flexibly composed for joint simulation. Experiments on PhysAssets and Google Scanned Objects demonstrate that, compared with existing methods, PhysForge provides stronger control over material-dependent physical responses while supporting component-level physical modeling for complex interactions. It achieves the best CLIP and physical controllability scores on both common and uncommon materials, with qualitative comparisons, component-level ablations, and a user study further supporting these improvements. Our project page is available at https://masterwanna.github.io/PhysForge.html .

Key facts. No citing papers in the map yet (data through 14 Oct 2026). Builds on 38 of its 41 references that are in the map. First posted on arXiv 9 Oct 2026.

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38 of 41 references.

References · 38

  1. 20233D Gaussian Splatting for Real-Time Radiance Field Renderingcited by 6,226
  2. 2025Wan: Open and Advanced Large-Scale Video Generative Modelscited by 2,708
  3. 2025SAM 3: Segment Anything with Conceptscited by 906
  4. 2024Structured 3D Latents for Scalable and Versatile 3D Generationcited by 770
  5. 2025Depth Anything 3: Recovering the Visual Space from Any Viewscited by 692
  6. 2022Google Scanned Objects: A High-Quality Dataset of 3D Scanned Household Itemscited by 612
  7. 2023FoundationPose: Unified 6D Pose Estimation and Tracking of Novel Objectscited by 429
  8. 2023PhysGaussian: Physics-Integrated 3D Gaussians for Generative Dynamicscited by 377
  9. 2025SAM 3D: 3Dfy Anything in Imagescited by 247
  10. 2024VideoPhy: Evaluating Physical Commonsense for Video Generationcited by 228
  11. 2024PhysDreamer: Physics-Based Interaction with 3D Objects via Video Generationcited by 191
  12. 2025Native and Compact Structured Latents for 3D Generationcited by 175
26 more
  1. 2024PhysGen: Rigid-Body Physics-Grounded Image-to-Video Generationcited by 174
  2. 2023PAC-NeRF: Physics Augmented Continuum Neural Radiance Fields for Geometry-Agnostic System Identificationcited by 154
  3. 2025PARTFIELD: Learning 3D Feature Fields for Part Segmentation and Beyondcited by 95
  4. 2025PhysTwin: Physics-Informed Reconstruction and Simulation of Deformable Objects from Videoscited by 87
  5. 2025PartCrafter: Structured 3D Mesh Generation via Compositional Latent Diffusion Transformerscited by 84
  6. 2024Physics3D: Learning Physical Properties of 3D Gaussians via Video Diffusioncited by 80
  7. 2024PhyT2V: LLM-Guided Iterative Self-Refinement for Physics-Grounded Text-to-Video Generationcited by 80
  8. 2025OmniPhysGS: 3D Constitutive Gaussians for General Physics-Based Dynamics Generationcited by 69
  9. 2024PartGen: Part-level 3D Generation and Reconstruction with Multi-View Diffusion Modelscited by 62
  10. 2024MotionCraft: Physics-based Zero-Shot Video Generationcited by 48
  11. 2025P3-SAM: Native 3D Part Segmentationcited by 43
  12. 2025PhysX-3D: Physical-Grounded 3D Asset Generationcited by 42
  13. 2024DreamPhysics: Learning Physics-Based 3D Dynamics with Video Diffusion Priorscited by 41
  14. 2025PhysX-Anything: Simulation-Ready Physical 3D Assets from Single Imagecited by 37
  15. 2026Inference-time Physics Alignment of Video Generative Models with Latent World Modelscited by 37
  16. 2025VISTA: A Test-Time Self-Improving Video Generation Agentcited by 31
  17. 2024GaussianProperty: Integrating Physical Properties to 3D Gaussians with LMMscited by 23
  18. 2025DecoupledGaussian: Object-Scene Decoupling for Physics-Based Interactioncited by 17
  19. 2026PhysRVG: Physics-Aware Unified Reinforcement Learning for Video Generative Modelscited by 17
  20. 2026Physical Simulator In-the-Loop Video Generationcited by 14
  21. 2026NEWTON: Agentic Planning for Physically Grounded Video Generationcited by 12
  22. 2025PhysGM: Large Physical Gaussian Model for Feed-Forward 4D Synthesiscited by 10
  23. 2025PhyMAGIC: Physical Motion-Aware Generative Inference with Confidence-guided LLMcited by 5
  24. 2025NeuSpring: Neural Spring Fields for Reconstruction and Simulation of Deformable Objects from Videoscited by 5
  25. 2025Photo3D: Advancing Photorealistic 3D Generation through Structure-Aligned Detail Enhancementcited by 2
  26. 2026DeforM: Reasoning-Guided Physics-Aware Video Generation via Spatial-Temporal Maskingcited by 1

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  1. 2024PhysFlow: Unleashing the Potential of Multi-modal Foundation Models and Video Diffusion for 4D Dynamic Physical Scene Simulation
  2. 2026PhysReal: Learning Real-World Deformable Object Physics via Hybrid Constitutive Modeling
  3. 2024PhysMotion: Physics-Grounded Dynamics From a Single Image
  4. 2026MPMWorlds: Material-Point-Method Simulations for Inferring and Extrapolating Physical Dynamics
  5. 2024Phys4DGen: Physics-Compliant 4D Generation with Multi-Material Composition Perception
  6. 2025MatMart: Material Reconstruction of 3D Objects via Diffusion
  7. 2026MotionPhysics: Learnable Motion Distillation for Text-Guided Simulation
  8. 2026Diffusion-Based Material Regularization for Physics-Based Inverse Rendering