mlsanityData to 7 Oct 2026

MeshDiffusion: Score-based Generative 3D Mesh Modeling

arXiv 2303.08133 ↗First posted 14 Mar 2023cs.GR cs.AI cs.CVcited by 198

Not on the map. Why?

Cited by 96 in Diffusion models, but placed by its own abstract, which didn’t fit.

Abstract (arXiv)

We consider the task of generating realistic 3D shapes, which is useful for a variety of applications such as automatic scene generation and physical simulation. Compared to other 3D representations like voxels and point clouds, meshes are more desirable in practice, because (1) they enable easy and arbitrary manipulation of shapes for relighting and simulation, and (2) they can fully leverage the power of modern graphics pipelines which are mostly optimized for meshes. Previous scalable methods for generating meshes typically rely on sub-optimal post-processing, and they tend to produce overly-smooth or noisy surfaces without fine-grained geometric details. To overcome these shortcomings, we take advantage of the graph structure of meshes and use a simple yet very effective generative modeling method to generate 3D meshes. Specifically, we represent meshes with deformable tetrahedral grids, and then train a diffusion model on this direct parametrization. We demonstrate the effectiveness of our model on multiple generative tasks.

Key facts. Cited by 198 papers in the map (data through 7 Oct 2026). Builds on 37 of its 60 references that are in the map. First posted on arXiv 14 Mar 2023.

Builds on

37 of 60 references.

References · 37

  1. 2020Denoising Diffusion Probabilistic Modelscited by 20,851
  2. 2015U-Net: Convolutional Networks for Biomedical Image Segmentationcited by 19,604
  3. 2021High-Resolution Image Synthesis with Latent Diffusion Modelscited by 18,694
  4. 2020Denoising Diffusion Implicit Modelscited by 9,655
  5. 2020Score-Based Generative Modeling through Stochastic Differential Equationscited by 8,964
  6. 2015ShapeNet: An Information-Rich 3D Model Repositorycited by 2,880
  7. 2018Large Scale GAN Training for High Fidelity Natural Image Synthesiscited by 2,609
  8. 2022Video Diffusion Modelscited by 2,280
  9. 2021Structured Denoising Diffusion Models in Discrete State-Spacescited by 1,665
  10. 2021Efficient Geometry-aware 3D Generative Adversarial Networkscited by 1,204
  11. 2020Training Generative Adversarial Networks with Limited Datacited by 1,184
  12. 2018Learning Implicit Fields for Generative Shape Modelingcited by 1,060
25 more
  1. 2020Learning Mesh-Based Simulation with Graph Networkscited by 840
  2. 2020pi-GAN: Periodic Implicit Generative Adversarial Networks for 3D-Aware Image Synthesiscited by 708
  3. 2020GRAF: Generative Radiance Fields for 3D-Aware Image Synthesiscited by 688
  4. 2018Pixel2Mesh: Generating 3D Mesh Models from Single RGB Imagescited by 649
  5. 2016Learning a Probabilistic Latent Space of Object Shapes via 3D Generative-Adversarial Modelingcited by 558
  6. 2022LION: Latent Point Diffusion Models for 3D Shape Generationcited by 552
  7. 2019PointFlow: 3D Point Cloud Generation with Continuous Normalizing Flowscited by 487
  8. 2021Deep Marching Tetrahedra: a Hybrid Representation for High-Resolution 3D Shape Synthesiscited by 459
  9. 2022GET3D: A Generative Model of High Quality 3D Textured Shapes Learned from Imagescited by 446
  10. 2017Neural 3D Mesh Renderercited by 437
  11. 2019Sliced Score Matching: A Scalable Approach to Density and Score Estimationcited by 381
  12. 2021Extracting Triangular 3D Models, Materials, and Lighting From Imagescited by 363
  13. 2018Learning Category-Specific Mesh Reconstruction from Image Collectionscited by 317
  14. 2023TEXTure: Text-Guided Texturing of 3D Shapescited by 303
  15. 2020PolyGen: An Autoregressive Generative Model of 3D Meshescited by 267
  16. 2021Shape As Points: A Differentiable Poisson Solvercited by 186
  17. 2019Unsupervised Learning of Probably Symmetric Deformable 3D Objects from Images in the Wildcited by 180
  18. 2020MeshSDF: Differentiable Iso-Surface Extractioncited by 112
  19. 2021NeRF-VAE: A Geometry Aware 3D Scene Generative Modelcited by 111
  20. 2022SDF-StyleGAN: Implicit SDF-Based StyleGAN for 3D Shape Generationcited by 92
  21. 2022Learning Smooth Neural Functions via Lipschitz Regularizationcited by 86
  22. 2017Variational Autoencoders for Deforming 3D Mesh Modelscited by 69
  23. 2020TetraTSDF: 3D human reconstruction from a single image with a tetrahedral outer shellcited by 18
  24. 2022Structural Causal 3D Reconstructioncited by 12
  25. 2022TetGAN: A Convolutional Neural Network for Tetrahedral Mesh Generationcited by 8

Built on by

Cited by year (2026 to 7 Oct)

Citing papers per year: 2023: 45; 2024: 79; 2025: 50; 2026: 24.

198 papers.

Sort:

By area:

  1. 2024LGM: Large Multi-View Gaussian Model for High-Resolution 3D Content Creationcited by 730
  2. 2023Wonder3D: Single Image to 3D using Cross-Domain Diffusioncited by 682
  3. 2023SyncDreamer: Generating Multiview-consistent Images from a Single-view Imagecited by 638
  4. 2024InstantMesh: Efficient 3D Mesh Generation from a Single Image with Sparse-view Large Reconstruction Modelscited by 421
  5. 2023Instant3D: Fast Text-to-3D with Sparse-View Generation and Large Reconstruction Modelcited by 376
  6. 2023One-2-3-45++: Fast Single Image to 3D Objects with Consistent Multi-View Generation and 3D Diffusioncited by 283
  7. 2023GaussianDreamer: Fast Generation from Text to 3D Gaussians by Bridging 2D and 3D Diffusion Modelscited by 255
  8. 2023MeshGPT: Generating Triangle Meshes with Decoder-Only Transformerscited by 254
  9. 2023RoboGen: Towards Unleashing Infinite Data for Automated Robot Learning via Generative Simulationcited by 206
  10. 2023Align Your Gaussians: Text-to-4D with Dynamic 3D Gaussians and Composed Diffusion Modelscited by 169
  11. 2023RichDreamer: A Generalizable Normal-Depth Diffusion Model for Detail Richness in Text-to-3Dcited by 168
  12. 2024CraftsMan3D: High-fidelity Mesh Generation with 3D Native Generation and Interactive Geometry Refinercited by 120
38 more
  1. 2023DiT-3D: Exploring Plain Diffusion Transformers for 3D Shape Generationcited by 110
  2. 2024MeshAnything V2: Artist-Created Mesh Generation With Adjacent Mesh Tokenizationcited by 102
  3. 2024MeshXL: Neural Coordinate Field for Generative 3D Foundation Modelscited by 100
  4. 20243DTopia-XL: Scaling High-quality 3D Asset Generation via Primitive Diffusioncited by 100
  5. 2023SlotDiffusion: Object-Centric Generative Modeling with Diffusion Modelscited by 85
  6. 2024EdgeRunner: Auto-regressive Auto-encoder for Artistic Mesh Generationcited by 84
  7. 2024BlockFusion: Expandable 3D Scene Generation using Latent Tri-plane Extrapolationcited by 81
  8. 2023Consistent-1-to-3: Consistent Image to 3D View Synthesis via Geometry-aware Diffusion Modelscited by 79
  9. 2023EpiDiff: Enhancing Multi-View Synthesis via Localized Epipolar-Constrained Diffusioncited by 72
  10. 20243DTopia: Large Text-to-3D Generation Model with Hybrid Diffusion Priorscited by 72
  11. 2024Scaling Mesh Generation via Compressive Tokenizationcited by 71
  12. 2024Towards Realistic Scene Generation with LiDAR Diffusion Modelscited by 67
  13. 2023PolyDiff: Generating 3D Polygonal Meshes with Diffusion Modelscited by 66
  14. 2024EchoScene: Indoor Scene Generation via Information Echo over Scene Graph Diffusioncited by 66
  15. 2024Position: Topological Deep Learning is the New Frontier for Relational Learningcited by 65
  16. 2024Advances in 3D Generation: A Surveycited by 62
  17. 2025DeepMesh: Auto-Regressive Artist-mesh Creation with Reinforcement Learningcited by 62
  18. 2024ComboVerse: Compositional 3D Assets Creation Using Spatially-Aware Diffusion Guidancecited by 59
  19. 2024SemCity: Semantic Scene Generation with Triplane Diffusioncited by 53
  20. 2023Direct2.5: Diverse Text-to-3D Generation via Multi-view 2.5D Diffusioncited by 50
  21. 2023Mosaic-SDF for 3D Generative Modelscited by 48
  22. 2023RenAIssance: A Survey into AI Text-to-Image Generation in the Era of Large Modelcited by 47
  23. 2024PivotMesh: Generic 3D Mesh Generation via Pivot Vertices Guidancecited by 47
  24. 2025Efficient Part-level 3D Object Generation via Dual Volume Packingcited by 47
  25. 2024VideoMV: Consistent Multi-View Generation Based on Large Video Generative Modelcited by 45
  26. 2024R3D-AD: Reconstruction via Diffusion for 3D Anomaly Detectioncited by 45
  27. 2024OctFusion: Octree-based Diffusion Models for 3D Shape Generationcited by 40
  28. 2024DynamicCity: Large-Scale 4D Occupancy Generation from Dynamic Scenescited by 37
  29. 2024GeoLRM: Geometry-Aware Large Reconstruction Model for High-Quality 3D Gaussian Generationcited by 35
  30. 2023PrimDiffusion: Volumetric Primitives Diffusion for 3D Human Generationcited by 33
  31. 2023Disentangled Clothed Avatar Generation from Text Descriptionscited by 33
  32. 2023UGG: Unified Generative Graspingcited by 30
  33. 2024Efficient Diversity-Preserving Diffusion Alignment via Gradient-Informed GFlowNetscited by 30
  34. 2024BELM: Bidirectional Explicit Linear Multi-step Sampler for Exact Inversion in Diffusion Modelscited by 29
  35. 2023HarmonyView: Harmonizing Consistency and Diversity in One-Image-to-3Dcited by 27
  36. 2024Hi3D: Pursuing High-Resolution Image-to-3D Generation with Video Diffusion Modelscited by 27
  37. 2025OctGPT: Octree-based Multiscale Autoregressive Models for 3D Shape Generationcited by 27
  38. 2023TOSS:High-quality Text-guided Novel View Synthesis from a Single Imagecited by 26

50 most cited of 198 All 198 (JSON)

Similar, not cited

Close in wording, no citation either way

  1. 2023Controllable Mesh Generation Through Sparse Latent Point Diffusion Models
  2. 2026Nexus: Native Mesh Generation with Diffusion
  3. 2023Consistent Mesh Diffusion
  4. 2025PartDiffuser: Part-wise 3D Mesh Generation via Discrete Diffusion
  5. 2024An Object is Worth 64x64 Pixels: Generating 3D Object via Image Diffusion
  6. 20213D Shape Generation and Completion through Point-Voxel Diffusion
  7. 2022TetraDiffusion: Tetrahedral Diffusion Models for 3D Shape Generation
  8. 2026ActionMesh: Animated 3D Mesh Generation with Temporal 3D Diffusion