mlsanityData to 7 Oct 2026

3DQD: Generalized Deep 3D Shape Prior via Part-Discretized Diffusion Process

arXiv 2303.10406 ↗First posted 18 Mar 2023cs.CV cs.AI cs.LGcited by 25

Not on the map. Why?

Abstract (arXiv)

We develop a generalized 3D shape generation prior model, tailored for multiple 3D tasks including unconditional shape generation, point cloud completion, and cross-modality shape generation, etc. On one hand, to precisely capture local fine detailed shape information, a vector quantized variational autoencoder (VQ-VAE) is utilized to index local geometry from a compactly learned codebook based on a broad set of task training data. On the other hand, a discrete diffusion generator is introduced to model the inherent structural dependencies among different tokens. In the meantime, a multi-frequency fusion module (MFM) is developed to suppress high-frequency shape feature fluctuations, guided by multi-frequency contextual information. The above designs jointly equip our proposed 3D shape prior model with high-fidelity, diverse features as well as the capability of cross-modality alignment, and extensive experiments have demonstrated superior performances on various 3D shape generation tasks.

Key facts. Cited by 25 papers in the map (data through 7 Oct 2026). Builds on 63 of its 74 references that are in the map. First posted on arXiv 18 Mar 2023.

Builds on

63 of 74 references.

References · 63

  1. 2015Deep Residual Learning for Image Recognitioncited by 51,809
  2. 2021Learning Transferable Visual Models From Natural Language Supervisioncited by 33,456
  3. 2020Denoising Diffusion Probabilistic Modelscited by 20,851
  4. 2021High-Resolution Image Synthesis with Latent Diffusion Modelscited by 18,694
  5. 2021Diffusion Models Beat GANs on Image Synthesiscited by 8,185
  6. 2022Hierarchical Text-Conditional Image Generation with CLIP Latentscited by 6,539
  7. 2018A Style-Based Generator Architecture for Generative Adversarial Networkscited by 5,986
  8. 2022Classifier-Free Diffusion Guidancecited by 5,717
  9. 2016PointNet: Deep Learning on Point Sets for 3D Classification and Segmentationcited by 5,223
  10. 2017Neural Discrete Representation Learningcited by 4,650
  11. 2021Zero-Shot Text-to-Image Generationcited by 4,276
  12. 2021Improved Denoising Diffusion Probabilistic Modelscited by 3,736
38 more
  1. 2021GLIDE: Towards Photorealistic Image Generation and Editing with Text-Guided Diffusion Modelscited by 3,595
  2. 2020Taming Transformers for High-Resolution Image Synthesiscited by 3,229
  3. 2015ShapeNet: An Information-Rich 3D Model Repositorycited by 2,880
  4. 2021SDEdit: Guided Image Synthesis and Editing with Stochastic Differential Equationscited by 1,903
  5. 2021Structured Denoising Diffusion Models in Discrete State-Spacescited by 1,665
  6. 2021Image Super-Resolution via Iterative Refinementcited by 1,506
  7. 2021Palette: Image-to-Image Diffusion Modelscited by 1,296
  8. 2021Cascaded Diffusion Models for High Fidelity Image Generationcited by 1,155
  9. 2021CrossViT: Cross-Attention Multi-Scale Vision Transformer for Image Classificationcited by 806
  10. 2021Vector Quantized Diffusion Model for Text-to-Image Synthesiscited by 773
  11. 2021Diffusion Probabilistic Models for 3D Point Cloud Generationcited by 734
  12. 2018Pixel2Mesh: Generating 3D Mesh Models from Single RGB Imagescited by 649
  13. 2021ILVR: Conditioning Method for Denoising Diffusion Probabilistic Modelscited by 634
  14. 2020WaveGrad: Estimating Gradients for Waveform Generationcited by 620
  15. 2021Argmax Flows and Multinomial Diffusion: Learning Categorical Distributionscited by 566
  16. 2022LION: Latent Point Diffusion Models for 3D Shape Generationcited by 552
  17. 2018AtlasNet: A Papier-Mach'e Approach to Learning 3D Surface Generationcited by 539
  18. 20213D Shape Generation and Completion through Point-Voxel Diffusioncited by 516
  19. 2019PointFlow: 3D Point Cloud Generation with Continuous Normalizing Flowscited by 487
  20. 2021Diffusion Autoencoders: Toward a Meaningful and Decodable Representationcited by 447
  21. 2018PCN: Point Completion Networkcited by 382
  22. 2019DISN: Deep Implicit Surface Network for High-quality Single-view 3D Reconstructioncited by 332
  23. 2021PoinTr: Diverse Point Cloud Completion with Geometry-Aware Transformerscited by 284
  24. 2020Learning Gradient Fields for Shape Generationcited by 245
  25. 2018Pix3D: Dataset and Methods for Single-Image 3D Shape Modelingcited by 218
  26. 2022AutoSDF: Shape Priors for 3D Completion, Reconstruction and Generationcited by 208
  27. 20193D Point Cloud Generative Adversarial Network Based on Tree Structured Graph Convolutionscited by 173
  28. 2018Text2Shape: Generating Shapes from Natural Language by Learning Joint Embeddingscited by 169
  29. 2019SDFDiff: Differentiable Rendering of Signed Distance Fields for 3D Shape Optimizationcited by 159
  30. 2022KNN-Diffusion: Image Generation via Large-Scale Retrievalcited by 135
  31. 2022Neural Wavelet-domain Diffusion for 3D Shape Generationcited by 132
  32. 2019PQ-NET: A Generative Part Seq2Seq Network for 3D Shapescited by 118
  33. 2022ShapeFormer: Transformer-based Shape Completion via Sparse Representationcited by 106
  34. 2019PointCleanNet: Learning to Denoise and Remove Outliers from Dense Point Cloudscited by 99
  35. 2020SoftFlow: Probabilistic Framework for Normalizing Flow on Manifoldscited by 97
  36. 2020Discrete Point Flow Networks for Efficient Point Cloud Generationcited by 87
  37. 2022SeedFormer: Patch Seeds based Point Cloud Completion with Upsample Transformercited by 83
  38. 2021SetVAE: Learning Hierarchical Composition for Generative Modeling of Set-Structured Datacited by 78

50 most cited of 63 All 63 (JSON)

Built on by

Cited by year (2026 to 7 Oct)

Citing papers per year: 2023: 4; 2024: 15; 2025: 5; 2026: 1.

25 papers.

Sort:

By area:

  1. 2024Structured 3D Latents for Scalable and Versatile 3D Generationcited by 742
  2. 20243DTopia-XL: Scaling High-quality 3D Asset Generation via Primitive Diffusioncited by 100
  3. 2023FocalDreamer: Text-driven 3D Editing via Focal-fusion Assemblycited by 75
  4. 2024Towards Realistic Scene Generation with LiDAR Diffusion Modelscited by 67
  5. 2024MeshFormer: High-Quality Mesh Generation with 3D-Guided Reconstruction Modelcited by 55
  6. 2024StereoDiffusion: Training-Free Stereo Image Generation Using Latent Diffusion Modelscited by 24
  7. 2024LaGeM: A Large Geometry Model for 3D Representation Learning and Diffusioncited by 16
  8. 2023InstructP2P: Learning to Edit 3D Point Clouds with Text Instructionscited by 14
  9. 2024Text-to-3D Shape Generationcited by 13
  10. 2024NeuSDFusion: A Spatial-Aware Generative Model for 3D Shape Completion, Reconstruction, and Generationcited by 13
  11. 2024SC-Diff: 3D Shape Completion with Latent Diffusion Modelscited by 10
  12. 2023CLIPXPlore: Coupled CLIP and Shape Spaces for 3D Shape Explorationcited by 9
13 more
  1. 2024Neural Residual Diffusion Models for Deep Scalable Vision Generationcited by 9
  2. 2023Surf-D: Generating High-Quality Surfaces of Arbitrary Topologies Using Diffusion Modelscited by 8
  3. 2024LAM3D: Large Image-Point-Cloud Alignment Model for 3D Reconstruction from Single Imagecited by 7
  4. 2024Multi-scale Latent Point Consistency Models for 3D Shape Generationcited by 6
  5. 2024Deep Learning for 3D Point Cloud Enhancement: A Surveycited by 4
  6. 2024GenUDC: High Quality 3D Mesh Generation with Unsigned Dual Contouring Representationcited by 3
  7. 2025DiffListener: Discrete Diffusion Model for Listener Generationcited by 2
  8. 2025A Continuous-Time Consistency Model for 3D Point Cloud Generationcited by 2
  9. 2025GuideFlow3D: Optimization-Guided Rectified Flow For Appearance Transfercited by 2
  10. 2025MESC-3D:Mining Effective Semantic Cues for 3D Reconstruction from a Single Imagecited by 1
  11. 2025DreamTexture: Shape from Virtual Texture with Analysis by Augmentationcited by 1
  12. 2024VP-LLM: Text-Driven 3D Volume Completion with Large Language Models through Patchificationcited by 0
  13. 2026Collision-Aware and Observation-Aligned Object-Centric Scene Reconstruction from Point Cloudcited by 0

Similar, not cited

Close in wording, no citation either way

  1. 2025BridgeShape: Latent Diffusion Schr"odinger Bridge for 3D Shape Completion
  2. 2025LTM3D: Bridging Token Spaces for Conditional 3D Generation with Auto-Regressive Diffusion Framework
  3. 2025Representing 3D Shapes With 64 Latent Vectors for 3D Diffusion Models
  4. 2023Michelangelo: Conditional 3D Shape Generation based on Shape-Image-Text Aligned Latent Representation
  5. 2025Evaluating Latent Generative Paradigms for High-Fidelity 3D Shape Completion from a Single Depth Image
  6. 2024Dora: Sampling and Benchmarking for 3D Shape Variational Auto-Encoders
  7. 2024Topology-Aware Latent Diffusion for 3D Shape Generation
  8. 2025Hyper3D: Efficient 3D Representation via Hybrid Triplane and Octree Feature for Enhanced 3D Shape Variational Auto-Encoders