mlsanityData to 14 Oct 2026

SOPHY: Learning to Generate Simulation-Ready Objects with Physical Materials

arXiv 2504.12684 ↗First posted 17 Apr 2025cs.GR cs.CVcited by 5

Not on the map. Why?

Abstract (arXiv)

We present SOPHY, a generative model for 3D physics-aware shape synthesis. Unlike existing 3D generative models that focus solely on static geometry or 4D models that produce physics-agnostic animations, our method jointly synthesizes shape, texture, and material properties related to physics-grounded dynamics, making the generated objects ready for simulations and interactive, dynamic environments. To train our model, we introduce a dataset of 3D objects annotated with detailed physical material attributes, along with an efficient pipeline for material annotation. Our method enables applications such as text-driven generation of interactive, physics-aware 3D objects and single-image reconstruction of physically plausible shapes. Furthermore, our experiments show that jointly modeling shape and material properties enhances the realism and fidelity of the generated shapes, improving performance on both generative geometry and physical plausibility.

Key facts. Cited by 5 papers in the map (data through 14 Oct 2026). Builds on 77 of its 95 references that are in the map. First posted on arXiv 17 Apr 2025.

Builds on

77 of 95 references.

References · 77

  1. 2017Attention Is All You Needcited by 60,361
  2. 2021Learning Transferable Visual Models From Natural Language Supervisioncited by 33,744
  3. 2021High-Resolution Image Synthesis with Latent Diffusion Modelscited by 18,863
  4. 2023DINOv2: Learning Robust Visual Features without Supervisioncited by 7,974
  5. 20233D Gaussian Splatting for Real-Time Radiance Field Renderingcited by 6,226
  6. 2024GPT-4o System Cardcited by 4,588
  7. 2017PointNet++: Deep Hierarchical Feature Learning on Point Sets in a Metric Spacecited by 4,401
  8. 2022Elucidating the Design Space of Diffusion-Based Generative Modelscited by 3,045
  9. 2022DreamFusion: Text-to-3D using 2D Diffusioncited by 3,025
  10. 2015ShapeNet: An Information-Rich 3D Model Repositorycited by 2,897
  11. 2019DeepSDF: Learning Continuous Signed Distance Functions for Shape Representationcited by 2,689
  12. 2023Stable Video Diffusion: Scaling Latent Video Diffusion Models to Large Datasetscited by 2,581
38 more
  1. 2018Occupancy Networks: Learning 3D Reconstruction in Function Spacecited by 2,041
  2. 2022Objaverse: A Universe of Annotated 3D Objectscited by 1,540
  3. 2022Magic3D: High-Resolution Text-to-3D Content Creationcited by 1,290
  4. 2018Learning Implicit Fields for Generative Shape Modelingcited by 1,060
  5. 2023LRM: Large Reconstruction Model for Single Image to 3Dcited by 849
  6. 2024Structured 3D Latents for Scalable and Versatile 3D Generationcited by 770
  7. 2022Google Scanned Objects: A High-Quality Dataset of 3D Scanned Household Itemscited by 612
  8. 2023Zero123++: a Single Image to Consistent Multi-view Diffusion Base Modelcited by 521
  9. 2021Deep Marching Tetrahedra: a Hybrid Representation for High-Resolution 3D Shape Synthesiscited by 460
  10. 20233DShape2VecSet: A 3D Shape Representation for Neural Fields and Generative Diffusion Modelscited by 458
  11. 2020Modular Primitives for High-Performance Differentiable Renderingcited by 441
  12. 2024InstantMesh: Efficient 3D Mesh Generation from a Single Image with Sparse-view Large Reconstruction Modelscited by 433
  13. 2023Shap-E: Generating Conditional 3D Implicit Functionscited by 385
  14. 2023PhysGaussian: Physics-Integrated 3D Gaussians for Generative Dynamicscited by 377
  15. 2021ABO: Dataset and Benchmarks for Real-World 3D Object Understandingcited by 366
  16. 2025Hunyuan3D 2.0: Scaling Diffusion Models for High Resolution Textured 3D Assets Generationcited by 356
  17. 20243D-VLA: A 3D Vision-Language-Action Generative World Modelcited by 328
  18. 2024GRM: Large Gaussian Reconstruction Model for Efficient 3D Reconstruction and Generationcited by 301
  19. 2024VideoPhy: Evaluating Physical Commonsense for Video Generationcited by 228
  20. 2019Texture Fields: Learning Texture Representations in Function Spacecited by 210
  21. 2023DreamGaussian4D: Generative 4D Gaussian Splattingcited by 194
  22. 2024PhysDreamer: Physics-Based Interaction with 3D Objects via Video Generationcited by 191
  23. 2024PhysGen: Rigid-Body Physics-Grounded Image-to-Video Generationcited by 174
  24. 2024CAT4D: Create Anything in 4D with Multi-View Video Diffusion Modelscited by 161
  25. 2023PAC-NeRF: Physics Augmented Continuum Neural Radiance Fields for Geometry-Agnostic System Identificationcited by 154
  26. 2024MeshAnything: Artist-Created Mesh Generation with Autoregressive Transformerscited by 144
  27. 2024DimensionX: Create Any 3D and 4D Scenes from a Single Image with Controllable Video Diffusioncited by 140
  28. 2023Paint3D: Paint Anything 3D with Lighting-Less Texture Diffusion Modelscited by 123
  29. 2024MeshAnything V2: Artist-Created Mesh Generation With Adjacent Mesh Tokenizationcited by 104
  30. 2024STAG4D: Spatial-Temporal Anchored Generative 4D Gaussianscited by 102
  31. 20243DTopia-XL: Scaling High-quality 3D Asset Generation via Primitive Diffusioncited by 101
  32. 2024Diffusion4D: Fast Spatial-temporal Consistent 4D Generation via Video Diffusion Modelscited by 100
  33. 2024Meta 3D AssetGen: Text-to-Mesh Generation with High-Quality Geometry, Texture, and PBR Materialscited by 66
  34. 2024Controlling Space and Time with Diffusion Modelscited by 66
  35. 2025PhysGen3D: Crafting a Miniature Interactive World from a Single Imagecited by 66
  36. 20244K4DGen: Panoramic 4D Generation at 4K Resolutioncited by 54
  37. 2025RigAnything: Template-Free Autoregressive Rigging for Diverse 3D Assetscited by 47
  38. 2024EG4D: Explicit Generation of 4D Object without Score Distillationcited by 45

50 most cited of 77 All 77 (JSON)

Built on by

Cited by year (2026 to 14 Oct)

Citing papers per year: 2026: 5.

5 papers.