mlsanityData to 7 Oct 2026

SDF-StyleGAN: Implicit SDF-Based StyleGAN for 3D Shape Generation

arXiv 2206.12055 ↗First posted 24 Jun 2022cs.CVcited by 92

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Cited by 28 in Diffusion models, but placed by its own abstract, which didn’t fit.

Abstract (arXiv)

We present a StyleGAN2-based deep learning approach for 3D shape generation, called SDF-StyleGAN, with the aim of reducing visual and geometric dissimilarity between generated shapes and a shape collection. We extend StyleGAN2 to 3D generation and utilize the implicit signed distance function (SDF) as the 3D shape representation, and introduce two novel global and local shape discriminators that distinguish real and fake SDF values and gradients to significantly improve shape geometry and visual quality. We further complement the evaluation metrics of 3D generative models with the shading-image-based Fr'echet inception distance (FID) scores to better assess visual quality and shape distribution of the generated shapes. Experiments on shape generation demonstrate the superior performance of SDF-StyleGAN over the state-of-the-art. We further demonstrate the efficacy of SDF-StyleGAN in various tasks based on GAN inversion, including shape reconstruction, shape completion from partial point clouds, single-view image-based shape generation, and shape style editing. Extensive ablation studies justify the efficacy of our framework design. Our code and trained models are available at https://github.com/Zhengxinyang/SDF-StyleGAN.

Key facts. Cited by 92 papers in the map (data through 7 Oct 2026). Builds on 65 of its 88 references that are in the map. First posted on arXiv 24 Jun 2022.

Builds on

65 of 88 references.

References · 65

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  2. 2020Denoising Diffusion Probabilistic Modelscited by 20,851
  3. 2018A Style-Based Generator Architecture for Generative Adversarial Networkscited by 5,986
  4. 2015Rethinking the Inception Architecture for Computer Visioncited by 5,451
  5. 2016PointNet: Deep Learning on Point Sets for 3D Classification and Segmentationcited by 5,223
  6. 2019Generative Modeling by Estimating Gradients of the Data Distributioncited by 4,067
  7. 2019Analyzing and Improving the Image Quality of StyleGANcited by 3,580
  8. 2015ShapeNet: An Information-Rich 3D Model Repositorycited by 2,880
  9. 2019DeepSDF: Learning Continuous Signed Distance Functions for Shape Representationcited by 2,682
  10. 2018Dynamic Graph CNN for Learning on Point Cloudscited by 2,220
  11. 2015Variational Inference with Normalizing Flowscited by 2,161
  12. 2018Occupancy Networks: Learning 3D Reconstruction in Function Spacecited by 2,037
38 more
  1. 2021Alias-Free Generative Adversarial Networkscited by 1,181
  2. 2018Learning Implicit Fields for Generative Shape Modelingcited by 1,060
  3. 2016Pixel Recurrent Neural Networkscited by 814
  4. 2020Convolutional Occupancy Networkscited by 760
  5. 2021Diffusion Probabilistic Models for 3D Point Cloud Generationcited by 734
  6. 2020pi-GAN: Periodic Implicit Generative Adversarial Networks for 3D-Aware Image Synthesiscited by 708
  7. 2018Which Training Methods for GANs do actually Converge?cited by 672
  8. 2018Pixel2Mesh: Generating 3D Mesh Models from Single RGB Imagescited by 649
  9. 20163D-R2N2: A Unified Approach for Single and Multi-view 3D Object Reconstructioncited by 587
  10. 2016Learning a Probabilistic Latent Space of Object Shapes via 3D Generative-Adversarial Modelingcited by 558
  11. 2018AtlasNet: A Papier-Mach'e Approach to Learning 3D Surface Generationcited by 539
  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. 2020InterFaceGAN: Interpreting the Disentangled Face Representation Learned by GANscited by 393
  15. 2020Local Implicit Grid Representations for 3D Scenescited by 372
  16. 2021StyleSDF: High-Resolution 3D-Consistent Image and Geometry Generationcited by 289
  17. 2021PoinTr: Diverse Point Cloud Completion with Geometry-Aware Transformerscited by 284
  18. 2020PolyGen: An Autoregressive Generative Model of 3D Meshescited by 267
  19. 2020Learning Gradient Fields for Shape Generationcited by 245
  20. 2022AutoSDF: Shape Priors for 3D Completion, Reconstruction and Generationcited by 208
  21. 2016A Theory of Generative ConvNetcited by 174
  22. 20193D Point Cloud Generative Adversarial Network Based on Tree Structured Graph Convolutionscited by 173
  23. 2019PQ-NET: A Generative Part Seq2Seq Network for 3D Shapescited by 118
  24. 2018PointGrow: Autoregressively Learned Point Cloud Generation with Self-Attentioncited by 105
  25. 2020SoftFlow: Probabilistic Framework for Normalizing Flow on Manifoldscited by 97
  26. 2020Discrete Point Flow Networks for Efficient Point Cloud Generationcited by 87
  27. 2018The Unusual Effectiveness of Averaging in GAN Trainingcited by 73
  28. 2022Dual Octree Graph Networks for Learning Adaptive Volumetric Shape Representationscited by 71
  29. 2021Deep Implicit Moving Least-Squares Functions for 3D Reconstructioncited by 67
  30. 2017Improved Adversarial Systems for 3D Object Generation and Reconstructioncited by 66
  31. 2019StructureNet: Hierarchical Graph Networks for 3D Shape Generationcited by 59
  32. 2020Generative PointNet: Deep Energy-Based Learning on Unordered Point Sets for 3D Generation, Reconstruction and Classificationcited by 57
  33. 2019C-Flow: Conditional Generative Flow Models for Images and 3D Point Cloudscited by 50
  34. 20213D Shape Generation with Grid-based Implicit Functionscited by 48
  35. 2020Adversarial Generation of Continuous Implicit Shape Representationscited by 46
  36. 2020Progressive Point Cloud Deconvolution Generation Networkcited by 46
  37. 2020DECOR-GAN: 3D Shape Detailization by Conditional Refinementcited by 45
  38. 2021Octree Transformer: Autoregressive 3D Shape Generation on Hierarchically Structured Sequencescited by 38

50 most cited of 65 All 65 (JSON)

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2022: 5; 2023: 30; 2024: 26; 2025: 19; 2026: 12.

92 papers.

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  1. 2024Structured 3D Latents for Scalable and Versatile 3D Generationcited by 742
  2. 20233DShape2VecSet: A 3D Shape Representation for Neural Fields and Generative Diffusion Modelscited by 449
  3. 20223D Neural Field Generation using Triplane Diffusioncited by 274
  4. 2023MeshDiffusion: Score-based Generative 3D Mesh Modelingcited by 198
  5. 20233DGen: Triplane Latent Diffusion for Textured Mesh Generationcited by 181
  6. 2022Dream3D: Zero-Shot Text-to-3D Synthesis Using 3D Shape Prior and Text-to-Image Diffusion Modelscited by 151
  7. 2023Let 2D Diffusion Model Know 3D-Consistency for Robust Text-to-3D Generationcited by 133
  8. 2022Neural Wavelet-domain Diffusion for 3D Shape Generationcited by 132
  9. 2023Locally Attentional SDF Diffusion for Controllable 3D Shape Generationcited by 129
  10. 2023Compositional 3D Scene Generation using Locally Conditioned Diffusioncited by 101
  11. 2025SparseFlex: High-Resolution and Arbitrary-Topology 3D Shape Modelingcited by 76
  12. 2023SALAD: Part-Level Latent Diffusion for 3D Shape Generation and Manipulationcited by 66
38 more
  1. 2024Advances in 3D Generation: A Surveycited by 62
  2. 2023Mosaic-SDF for 3D Generative Modelscited by 48
  3. 2023Controllable Mesh Generation Through Sparse Latent Point Diffusion Modelscited by 40
  4. 2024OctFusion: Octree-based Diffusion Models for 3D Shape Generationcited by 40
  5. 2023DiffComplete: Diffusion-based Generative 3D Shape Completioncited by 35
  6. 2024An Object is Worth 64x64 Pixels: Generating 3D Object via Image Diffusioncited by 34
  7. 2025Gaussian Variation Field Diffusion for High-fidelity Video-to-4D Synthesiscited by 33
  8. 2025NANO3D: A Training-Free Approach for Efficient 3D Editing Without Maskscited by 29
  9. 2023Neural Wavelet-domain Diffusion for 3D Shape Generation, Inversion, and Manipulationcited by 27
  10. 2025OctGPT: Octree-based Multiscale Autoregressive Models for 3D Shape Generationcited by 27
  11. 2024Make-A-Shape: a Ten-Million-scale 3D Shape Modelcited by 25
  12. 2023Ghost on the Shell: An Expressive Representation of General 3D Shapescited by 24
  13. 2024PhysPart: Physically Plausible Part Completion for Interactable Objectscited by 24
  14. 2024MVD2: Efficient Multiview 3D Reconstruction for Multiview Diffusioncited by 22
  15. 2023Chupa: Carving 3D Clothed Humans from Skinned Shape Priors using 2D Diffusion Probabilistic Modelscited by 20
  16. 2023Get3DHuman: Lifting StyleGAN-Human into a 3D Generative Model using Pixel-aligned Reconstruction Priorscited by 19
  17. 2025LL3M: Large Language 3D Modelerscited by 18
  18. 2024Geometry Image Diffusion: Fast and Data-Efficient Text-to-3D with Image-Based Surface Representationcited by 17
  19. 20243D Mesh Editing using Masked LRMscited by 17
  20. 2024DDMI: Domain-Agnostic Latent Diffusion Models for Synthesizing High-Quality Implicit Neural Representationscited by 16
  21. 2024Atlas Gaussians Diffusion for 3D Generationcited by 15
  22. 2022TetraDiffusion: Tetrahedral Diffusion Models for 3D Shape Generationcited by 14
  23. 2023Doodle Your 3D: From Abstract Freehand Sketches to Precise 3D Shapescited by 14
  24. 2024Topology-Aware Latent Diffusion for 3D Shape Generationcited by 13
  25. 2024Text-to-3D Shape Generationcited by 13
  26. 2024NeuSDFusion: A Spatial-Aware Generative Model for 3D Shape Completion, Reconstruction, and Generationcited by 13
  27. 2025iFlame: Interleaving Full and Linear Attention for Efficient Mesh Generationcited by 13
  28. 20233D VR Sketch Guided 3D Shape Prototyping and Explorationcited by 12
  29. 2023CLIPXPlore: Coupled CLIP and Shape Spaces for 3D Shape Explorationcited by 9
  30. 2025Learning-based 3D Reconstruction in Autonomous Driving: A Comprehensive Surveycited by 9
  31. 2023NaviNeRF: NeRF-based 3D Representation Disentanglement by Latent Semantic Navigationcited by 8
  32. 2023SENS: Part-Aware Sketch-based Implicit Neural Shape Modelingcited by 8
  33. 2023Progressive Text-to-3D Generation for Automatic 3D Prototypingcited by 8
  34. 2024GetMesh: A Controllable Model for High-quality Mesh Generation and Manipulationcited by 8
  35. 2024Assessing Sample Quality via the Latent Space of Generative Modelscited by 8
  36. 2024DetailGen3D: Generative 3D Geometry Enhancement via Data-Dependent Flowcited by 8
  37. 2024Coherent 3D Scene Diffusion From a Single RGB Imagecited by 8
  38. 2024LAM3D: Large Image-Point-Cloud Alignment Model for 3D Reconstruction from Single Imagecited by 7

50 most cited of 92 All 92 (JSON)