mlsanityData to 7 Oct 2026

Learning Gradient Fields for Shape Generation

arXiv 2008.06520 ↗First posted 14 Aug 2020cs.CV cs.LGcited by 245

Not on the map. Why?

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

Abstract (arXiv)

In this work, we propose a novel technique to generate shapes from point cloud data. A point cloud can be viewed as samples from a distribution of 3D points whose density is concentrated near the surface of the shape. Point cloud generation thus amounts to moving randomly sampled points to high-density areas. We generate point clouds by performing stochastic gradient ascent on an unnormalized probability density, thereby moving sampled points toward the high-likelihood regions. Our model directly predicts the gradient of the log density field and can be trained with a simple objective adapted from score-based generative models. We show that our method can reach state-of-the-art performance for point cloud auto-encoding and generation, while also allowing for extraction of a high-quality implicit surface. Code is available at https://github.com/RuojinCai/ShapeGF.

Key facts. Cited by 245 papers in the map (data through 7 Oct 2026). First posted on arXiv 14 Aug 2020.

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Citing papers per year: 2020: 1; 2021: 36; 2022: 54; 2023: 63; 2024: 47; 2025: 28; 2026: 16.

245 papers.

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  1. 2022DreamFusion: Text-to-3D using 2D Diffusioncited by 3,006
  2. 2021Image Super-Resolution via Iterative Refinementcited by 1,506
  3. 2021Palette: Image-to-Image Diffusion Modelscited by 1,296
  4. 2022Diffusion Models: A Comprehensive Survey of Methods and Applicationscited by 1,107
  5. 2021Diffusion Probabilistic Models for 3D Point Cloud Generationcited by 734
  6. 2022Point-E: A System for Generating 3D Point Clouds from Complex Promptscited by 694
  7. 2021Maximum Likelihood Training of Score-Based Diffusion Modelscited by 670
  8. 2021Score-based Generative Modeling in Latent Spacecited by 634
  9. 2022Score Jacobian Chaining: Lifting Pretrained 2D Diffusion Models for 3D Generationcited by 597
  10. 2021Diffusion Schr"odinger Bridge with Applications to Score-Based Generative Modelingcited by 594
  11. 2022LION: Latent Point Diffusion Models for 3D Shape Generationcited by 552
  12. 20213D Shape Generation and Completion through Point-Voxel Diffusioncited by 516
38 more
  1. 2021Zero-Shot Text-Guided Object Generation with Dream Fieldscited by 513
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  3. 2023ResShift: Efficient Diffusion Model for Image Super-resolution by Residual Shiftingcited by 360
  4. 2022Rodin: A Generative Model for Sculpting 3D Digital Avatars Using Diffusioncited by 309
  5. 2022Score-based Generative Modeling of Graphs via the System of Stochastic Differential Equationscited by 273
  6. 2021How to Train Your Energy-Based Modelscited by 271
  7. 2021Crystal Diffusion Variational Autoencoder for Periodic Material Generationcited by 268
  8. 2021DeepCAD: A Deep Generative Network for Computer-Aided Design Modelscited by 266
  9. 2023Q-Diffusion: Quantizing Diffusion Modelscited by 266
  10. 2023MeshGPT: Generating Triangle Meshes with Decoder-Only Transformerscited by 254
  11. 2023Michelangelo: Conditional 3D Shape Generation based on Shape-Image-Text Aligned Latent Representationcited by 225
  12. 2022DiffRF: Rendering-Guided 3D Radiance Field Diffusioncited by 204
  13. 2023Generative Diffusion Prior for Unified Image Restoration and Enhancementcited by 198
  14. 2022From data to functa: Your data point is a function and you can treat it like onecited by 183
  15. 2021A Variational Perspective on Diffusion-Based Generative Models and Score Matchingcited by 182
  16. 2022Learning Fast Samplers for Diffusion Models by Differentiating Through Sample Qualitycited by 181
  17. 2023UFOGen: You Forward Once Large Scale Text-to-Image Generation via Diffusion GANscited by 165
  18. 2022Generative Modelling With Inverse Heat Dissipationcited by 164
  19. 2022Dream3D: Zero-Shot Text-to-3D Synthesis Using 3D Shape Prior and Text-to-Image Diffusion Modelscited by 151
  20. 2022Diffusion Models for Video Prediction and Infillingcited by 134
  21. 2022Neural Wavelet-domain Diffusion for 3D Shape Generationcited by 132
  22. 2024Lumina-Next: Making Lumina-T2X Stronger and Faster with Next-DiTcited by 130
  23. 2021Learning to Efficiently Sample from Diffusion Probabilistic Modelscited by 129
  24. 2023Locally Attentional SDF Diffusion for Controllable 3D Shape Generationcited by 129
  25. 2022GENIE: Higher-Order Denoising Diffusion Solverscited by 127
  26. 2023Text2NeRF: Text-Driven 3D Scene Generation with Neural Radiance Fieldscited by 122
  27. 2022Score-Based Generative Models Detect Manifoldscited by 121
  28. 2023DiT-3D: Exploring Plain Diffusion Transformers for 3D Shape Generationcited by 110
  29. 2022Diffusion-based Molecule Generation with Informative Prior Bridgescited by 104
  30. 2022DifFace: Blind Face Restoration with Diffused Error Contractioncited by 96
  31. 2022SDF-StyleGAN: Implicit SDF-Based StyleGAN for 3D Shape Generationcited by 92
  32. 2022POCO: Point Convolution for Surface Reconstructioncited by 91
  33. 2022Learning to Generate Realistic LiDAR Point Cloudscited by 91
  34. 2023DiffuRec: A Diffusion Model for Sequential Recommendationcited by 91
  35. 2021Generative Models as Distributions of Functionscited by 89
  36. 2021Score-Based Point Cloud Denoisingcited by 83
  37. 2021Diffusion Normalizing Flowcited by 77
  38. 2021SCALE: Modeling Clothed Humans with a Surface Codec of Articulated Local Elementscited by 72

50 most cited of 245 All 245 (JSON)

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  1. 2025StrucADT: Generating Structure-controlled 3D Point Clouds with Adjacency Diffusion Transformer
  2. 2026BuildAnyPoint: 3D Building Structured Abstraction from Diverse Point Clouds
  3. 2023Point Cloud Pre-training with Diffusion Models
  4. 2025PDT: Point Distribution Transformation with Diffusion Models
  5. 2023Point-Cloud Completion with Pretrained Text-to-image Diffusion Models
  6. 2026Learning Point Cloud Geometry as a Statistical Manifold: Theory and Practice ↗
  7. 2021A Conditional Point Diffusion-Refinement Paradigm for 3D Point Cloud Completion
  8. 2025Generative Data Augmentation for Object Point Cloud Segmentation