mlsanityData to 14 Oct 2026

HyperDiffusion: Generating Implicit Neural Fields with Weight-Space Diffusion

arXiv 2303.17015 ↗First posted 29 Mar 2023cs.CV cs.LGcited by 152

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Cited by 53 in Diffusion models, but placed by its own abstract, which didn’t fit.

Abstract (arXiv)

Implicit neural fields, typically encoded by a multilayer perceptron (MLP) that maps from coordinates (e.g., xyz) to signals (e.g., signed distances), have shown remarkable promise as a high-fidelity and compact representation. However, the lack of a regular and explicit grid structure also makes it challenging to apply generative modeling directly on implicit neural fields in order to synthesize new data. To this end, we propose HyperDiffusion, a novel approach for unconditional generative modeling of implicit neural fields. HyperDiffusion operates directly on MLP weights and generates new neural implicit fields encoded by synthesized MLP parameters. Specifically, a collection of MLPs is first optimized to faithfully represent individual data samples. Subsequently, a diffusion process is trained in this MLP weight space to model the underlying distribution of neural implicit fields. HyperDiffusion enables diffusion modeling over a implicit, compact, and yet high-fidelity representation of complex signals across 3D shapes and 4D mesh animations within one single unified framework.

Key facts. Cited by 152 papers in the map (data through 14 Oct 2026). Builds on 43 of its 54 references that are in the map. First posted on arXiv 29 Mar 2023.

Builds on

43 of 54 references.

References · 43

  1. 2020Denoising Diffusion Probabilistic Modelscited by 21,076
  2. 2021High-Resolution Image Synthesis with Latent Diffusion Modelscited by 18,863
  3. 2020Denoising Diffusion Implicit Modelscited by 9,781
  4. 2021Diffusion Models Beat GANs on Image Synthesiscited by 8,255
  5. 2022Photorealistic Text-to-Image Diffusion Models with Deep Language Understandingcited by 6,355
  6. 2018A Style-Based Generator Architecture for Generative Adversarial Networkscited by 6,013
  7. 2022Generative Adversarial Networkscited by 5,627
  8. 2017PointNet++: Deep Hierarchical Feature Learning on Point Sets in a Metric Spacecited by 4,401
  9. 2021GLIDE: Towards Photorealistic Image Generation and Editing with Text-Guided Diffusion Modelscited by 3,614
  10. 2019Analyzing and Improving the Image Quality of StyleGANcited by 3,588
  11. 2022DreamFusion: Text-to-3D using 2D Diffusioncited by 3,025
  12. 2015ShapeNet: An Information-Rich 3D Model Repositorycited by 2,897
31 more
  1. 2019DeepSDF: Learning Continuous Signed Distance Functions for Shape Representationcited by 2,689
  2. 2022Video Diffusion Modelscited by 2,305
  3. 2020Implicit Neural Representations with Periodic Activation Functionscited by 2,238
  4. 2020Fourier Features Let Networks Learn High Frequency Functions in Low Dimensional Domainscited by 2,200
  5. 2021Efficient Geometry-aware 3D Generative Adversarial Networkscited by 1,205
  6. 2021Alias-Free Generative Adversarial Networkscited by 1,184
  7. 2022Human Motion Diffusion Modelcited by 1,080
  8. 2020Convolutional Occupancy Networkscited by 761
  9. 2021Diffusion Probabilistic Models for 3D Point Cloud Generationcited by 735
  10. 2020pi-GAN: Periodic Implicit Generative Adversarial Networks for 3D-Aware Image Synthesiscited by 708
  11. 2022LION: Latent Point Diffusion Models for 3D Shape Generationcited by 553
  12. 20213D Shape Generation and Completion through Point-Voxel Diffusioncited by 516
  13. 2022StyleGAN-XL: Scaling StyleGAN to Large Diverse Datasetscited by 492
  14. 20233DShape2VecSet: A 3D Shape Representation for Neural Fields and Generative Diffusion Modelscited by 458
  15. 2022GET3D: A Generative Model of High Quality 3D Textured Shapes Learned from Imagescited by 446
  16. 2020Local Implicit Grid Representations for 3D Scenescited by 373
  17. 2020Deep Local Shapes: Learning Local SDF Priors for Detailed 3D Reconstructioncited by 321
  18. 20223D Neural Field Generation using Triplane Diffusioncited by 274
  19. 2023Text-To-4D Dynamic Scene Generationcited by 205
  20. 2022DiffRF: Rendering-Guided 3D Radiance Field Diffusioncited by 204
  21. 2018CodeSLAM - Learning a Compact, Optimisable Representation for Dense Visual SLAMcited by 152
  22. 2022GAUDI: A Neural Architect for Immersive 3D Scene Generationcited by 136
  23. 2022Diffusion-SDF: Conditional Generative Modeling of Signed Distance Functionscited by 133
  24. 20214DComplete: Non-Rigid Motion Estimation Beyond the Observable Surfacecited by 124
  25. 2021Generative Models as Distributions of Functionscited by 89
  26. 2022Learning to Learn with Generative Models of Neural Network Checkpointscited by 86
  27. 2022Texturify: Generating Textures on 3D Shape Surfacescited by 65
  28. 2022Generative Multiplane Images: Making a 2D GAN 3D-Awarecited by 57
  29. 2020Adversarial Generation of Continuous Implicit Shape Representationscited by 46
  30. 2021Learning Signal-Agnostic Manifolds of Neural Fieldscited by 45
  31. 2023Diffusion Probabilistic Fieldscited by 28

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Cited by year (2026 to 14 Oct)

Citing papers per year: 2023: 28; 2024: 70; 2025: 35; 2026: 19.

152 papers.

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  1. 2023Wonder3D: Single Image to 3D using Cross-Domain Diffusioncited by 689
  2. 2023SyncDreamer: Generating Multiview-consistent Images from a Single-view Imagecited by 645
  3. 2023Shap-E: Generating Conditional 3D Implicit Functionscited by 385
  4. 2023One-2-3-45++: Fast Single Image to 3D Objects with Consistent Multi-View Generation and 3D Diffusioncited by 283
  5. 2023MeshGPT: Generating Triangle Meshes with Decoder-Only Transformerscited by 259
  6. 2023RichDreamer: A Generalizable Normal-Depth Diffusion Model for Detail Richness in Text-to-3Dcited by 168
  7. 2023State of the Art on Diffusion Models for Visual Computingcited by 127
  8. 2023HiFA: High-fidelity Text-to-3D Generation with Advanced Diffusion Guidancecited by 110
  9. 20244Diffusion: Multi-view Video Diffusion Model for 4D Generationcited by 104
  10. 2024EscherNet: A Generative Model for Scalable View Synthesiscited by 95
  11. 2024BlockFusion: Expandable 3D Scene Generation using Latent Tri-plane Extrapolationcited by 83
  12. 2024Not All Noises Are Created Equally:Diffusion Noise Selection and Optimizationcited by 71
38 more
  1. 2024Towards Realistic Scene Generation with LiDAR Diffusion Modelscited by 69
  2. 2023LooseControl: Lifting ControlNet for Generalized Depth Conditioningcited by 68
  3. 2024Advances in 3D Generation: A Surveycited by 63
  4. 2024SPAD : Spatially Aware Multiview Diffuserscited by 62
  5. 2024Graph Neural Networks for Learning Equivariant Representations of Neural Networkscited by 59
  6. 2023Graph Metanetworks for Processing Diverse Neural Architecturescited by 57
  7. 2024VFusion3D: Learning Scalable 3D Generative Models from Video Diffusion Modelscited by 56
  8. 2024LT3SD: Latent Trees for 3D Scene Diffusioncited by 55
  9. 2024AGG: Amortized Generative 3D Gaussians for Single Image to 3Dcited by 53
  10. 2024TextureDreamer: Image-guided Texture Synthesis through Geometry-aware Diffusioncited by 52
  11. 2024PivotMesh: Generic 3D Mesh Generation via Pivot Vertices Guidancecited by 50
  12. 2023DiffCAD: Weakly-Supervised Probabilistic CAD Model Retrieval and Alignment from an RGB Imagecited by 48
  13. 2024DressCode: Autoregressively Sewing and Generating Garments from Text Guidancecited by 44
  14. 2024OctFusion: Octree-based Diffusion Models for 3D Shape Generationcited by 43
  15. 2024Neural Network Diffusioncited by 42
  16. 2024MeshArt: Generating Articulated Meshes with Structure-Guided Transformerscited by 41
  17. 2025PhysCtrl: Generative Physics for Controllable and Physics-Grounded Video Generationcited by 41
  18. 2024Interpreting the Weight Space of Customized Diffusion Modelscited by 36
  19. 2025Noise Hypernetworks: Amortizing Test-Time Compute in Diffusion Modelscited by 35
  20. 2025OctGPT: Octree-based Multiscale Autoregressive Models for 3D Shape Generationcited by 30
  21. 2024CharacterGen: Efficient 3D Character Generation from Single Images with Multi-View Pose Canonicalizationcited by 28
  22. 2024Recent Trends in 3D Reconstruction of General Non-Rigid Scenescited by 28
  23. 2024Sat2Scene: 3D Urban Scene Generation from Satellite Images with Diffusioncited by 27
  24. 2023NAP: Neural 3D Articulation Priorcited by 25
  25. 2025We Should Chart an Atlas of All the World's Modelscited by 25
  26. 2023Text-to-3D Generation with Bidirectional Diffusion using both 2D and 3D priorscited by 24
  27. 2024SceneFactor: Factored Latent 3D Diffusion for Controllable 3D Scene Generationcited by 24
  28. 2024ArtFormer: Controllable Generation of Diverse 3D Articulated Objectscited by 22
  29. 2024Atlas3D: Physically Constrained Self-Supporting Text-to-3D for Simulation and Fabricationcited by 20
  30. 2025FunDiff: Diffusion Models over Function Spaces for Physics-Informed Generative Modelingcited by 20
  31. 2025MeshLLM: Empowering Large Language Models to Progressively Understand and Generate 3D Meshcited by 20
  32. 2025TR-DQ: Time-Rotation Diffusion Quantizationcited by 19
  33. 2024Monomial Matrix Group Equivariant Neural Functional Networkscited by 17
  34. 2024Deep Linear Probe Generators for Weight Space Learningcited by 17
  35. 2023ProtoDiff: Learning to Learn Prototypical Networks by Task-Guided Diffusioncited by 16
  36. 2024DDMI: Domain-Agnostic Latent Diffusion Models for Synthesizing High-Quality Implicit Neural Representationscited by 16
  37. 2024Conditional LoRA Parameter Generationcited by 16
  38. 2024LaGeM: A Large Geometry Model for 3D Representation Learning and Diffusioncited by 16

50 most cited of 152 All 152 (JSON)

Similar, not cited

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  1. 2023HoloDiffusion: Training a 3D Diffusion Model using 2D Images
  2. 2025HyperDiffusionFields (HyDiF): Diffusion-Guided Hypernetworks for Learning Implicit Molecular Neural Fields
  3. 20223D-LDM: Neural Implicit 3D Shape Generation with Latent Diffusion Models
  4. 2026HyperbolicDiffusion: Sharp & Scalable Tiled Generation on the Hyperbolic Plane
  5. 2022SinDiffusion: Learning a Diffusion Model from a Single Natural Image
  6. 2023Single Mesh Diffusion Models with Field Latents for Texture Generation
  7. 2023NeuralField-LDM: Scene Generation with Hierarchical Latent Diffusion Models
  8. 2023Efficient-3DiM: Learning a Generalizable Single-image Novel-view Synthesizer in One Day