mlsanityData to 7 Oct 2026

TetraDiffusion: Tetrahedral Diffusion Models for 3D Shape Generation

arXiv 2211.13220 ↗First posted 23 Nov 2022cs.CV cs.GR cs.LGcited by 14

On the map: Diffusion models → 3D, point cloud and scene generation

Abstract (arXiv)

Probabilistic denoising diffusion models (DDMs) have set a new standard for 2D image generation. Extending DDMs for 3D content creation is an active field of research. Here, we propose TetraDiffusion, a diffusion model that operates on a tetrahedral partitioning of 3D space to enable efficient, high-resolution 3D shape generation. Our model introduces operators for convolution and transpose convolution that act directly on the tetrahedral partition, and seamlessly includes additional attributes such as color. Remarkably, TetraDiffusion enables rapid sampling of detailed 3D objects in nearly real-time with unprecedented resolution. It's also adaptable for generating 3D shapes conditioned on 2D images. Compared to existing 3D mesh diffusion techniques, our method is up to 200 times faster in inference speed, works on standard consumer hardware, and delivers superior results.

Key facts. Cited by 14 papers in the map (data through 7 Oct 2026). Placed in 3D, point cloud and scene generation, one of 14 directions in Diffusion models. Builds on 41 of its 61 references that are in the map. First posted on arXiv 23 Nov 2022.

Builds on

41 of 61 references.

Closest ancestors · 2

Same direction, newest first

  1. 2022LION: Latent Point Diffusion Models for 3D Shape Generation12 Oct
  2. 2021Diffusion Probabilistic Models for 3D Point Cloud Generation2 Mar

Other references · 39

  1. 2021Learning Transferable Visual Models From Natural Language Supervisioncited by 33,456
  2. 2020Denoising Diffusion Probabilistic Modelscited by 20,851
  3. 2015U-Net: Convolutional Networks for Biomedical Image Segmentationcited by 19,604
  4. 2021High-Resolution Image Synthesis with Latent Diffusion Modelscited by 18,694
  5. 2016Semi-Supervised Classification with Graph Convolutional Networkscited by 11,282
  6. 2020Denoising Diffusion Implicit Modelscited by 9,655
  7. 2020Score-Based Generative Modeling through Stochastic Differential Equationscited by 8,964
  8. 2021Diffusion Models Beat GANs on Image Synthesiscited by 8,185
  9. 2022Hierarchical Text-Conditional Image Generation with CLIP Latentscited by 6,539
  10. 2022Photorealistic Text-to-Image Diffusion Models with Deep Language Understandingcited by 6,322
  11. 2022Classifier-Free Diffusion Guidancecited by 5,717
  12. 2021GLIDE: Towards Photorealistic Image Generation and Editing with Text-Guided Diffusion Modelscited by 3,595
27 more
  1. 2016Gaussian Error Linear Units (GELUs)cited by 3,431
  2. 2015ShapeNet: An Information-Rich 3D Model Repositorycited by 2,880
  3. 2017FiLM: Visual Reasoning with a General Conditioning Layercited by 2,286
  4. 2018Group Normalizationcited by 1,514
  5. 2019Simplifying Graph Convolutional Networkscited by 1,470
  6. 2020Linformer: Self-Attention with Linear Complexitycited by 1,462
  7. 2019KPConv: Flexible and Deformable Convolution for Point Cloudscited by 1,202
  8. 2021Variational Diffusion Modelscited by 1,145
  9. 2013Spectral Networks and Locally Connected Networks on Graphscited by 1,097
  10. 2018Learning Implicit Fields for Generative Shape Modelingcited by 1,060
  11. 2021CrossViT: Cross-Attention Multi-Scale Vision Transformer for Image Classificationcited by 806
  12. 20213D Shape Generation and Completion through Point-Voxel Diffusioncited by 516
  13. 2019PointFlow: 3D Point Cloud Generation with Continuous Normalizing Flowscited by 487
  14. 2021Deep Marching Tetrahedra: a Hybrid Representation for High-Resolution 3D Shape Synthesiscited by 459
  15. 2022GET3D: A Generative Model of High Quality 3D Textured Shapes Learned from Imagescited by 446
  16. 2020Modular Primitives for High-Performance Differentiable Renderingcited by 439
  17. 2021Extracting Triangular 3D Models, Materials, and Lighting From Imagescited by 363
  18. 2022Understanding Diffusion Models: A Unified Perspectivecited by 337
  19. 2020Learning Gradient Fields for Shape Generationcited by 245
  20. 2021Shape As Points: A Differentiable Poisson Solvercited by 186
  21. 2022Neural Wavelet-domain Diffusion for 3D Shape Generationcited by 132
  22. 2016Generative and Discriminative Voxel Modeling with Convolutional Neural Networkscited by 128
  23. 2022SDF-StyleGAN: Implicit SDF-Based StyleGAN for 3D Shape Generationcited by 92
  24. 2018Multiresolution Tree Networks for 3D Point Cloud Processingcited by 91
  25. 2020Learning Deformable Tetrahedral Meshes for 3D Reconstructioncited by 84
  26. 2022TetGAN: A Convolutional Neural Network for Tetrahedral Mesh Generationcited by 8
  27. 2021Lecture notes on high-dimensional datacited by 5

Built on by

Cited by year (2026 to 7 Oct)

Citing papers per year: 2023: 6; 2024: 3; 2025: 3; 2026: 2.

14 papers.

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  1. 2023Align Your Gaussians: Text-to-4D with Dynamic 3D Gaussians and Composed Diffusion Modelscited by 169
  2. 2023TexFusion: Synthesizing 3D Textures with Text-Guided Image Diffusion Modelscited by 86
  3. 2024Advances in 3D Generation: A Surveycited by 62
  4. 2024VideoMV: Consistent Multi-View Generation Based on Large Video Generative Modelcited by 45
  5. 2025CubeDiff: Repurposing Diffusion-Based Image Models for Panorama Generationcited by 35
  6. 2023Multi-modal Machine Learning in Engineering Design: A Review and Future Directionscited by 27
  7. 2023WildFusion: Learning 3D-Aware Latent Diffusion Models in View Spacecited by 8
  8. 2023DiffPMAE: Diffusion Masked Autoencoders for Point Cloud Reconstructioncited by 4
  9. 2023Efficient Meshy Neural Fields for Animatable Human Avatarscited by 2
  10. 2024GALA: Geometry-Aware Local Adaptive Grids for Detailed 3D Generationcited by 1
  11. 2025A Mesh Is Worth 512 Numbers: Spectral-domain Diffusion Modeling for High-dimension Shape Generationcited by 1
  12. 20253D Shape Generation: A Surveycited by 0
2 more
  1. 2026Rethinking 3D Shape Generation: Diffusion over Superquadricscited by 0
  2. 2026PLSR: Progressive and Localized Super-Resolution of 3D Objects via Localized Latent Voxel Diffusioncited by 0

Similar, not cited

Close in wording, no citation either way

  1. 2022RenderDiffusion: Image Diffusion for 3D Reconstruction, Inpainting and Generation
  2. 2023DiT-3D: Exploring Plain Diffusion Transformers for 3D Shape Generation
  3. 2023PolyDiff: Generating 3D Polygonal Meshes with Diffusion Models
  4. 2023HoloDiffusion: Training a 3D Diffusion Model using 2D Images
  5. 2022IC3D: Image-Conditioned 3D Diffusion for Shape Generation
  6. 2023PolyDiffuse: Polygonal Shape Reconstruction via Guided Set Diffusion Models
  7. 2024Diffusion Models in 3D Vision: A Survey
  8. 2023Sin3DM: Learning a Diffusion Model from a Single 3D Textured Shape