mlsanityData to 14 Oct 2026

3D Shape Induction from 2D Views of Multiple Objects

arXiv 1612.05872 ↗First posted 18 Dec 2016cs.CVcited by 121

Not on the map. Why?

Cited by 21 in Diffusion models, but placed by its own abstract, which didn’t fit.

Abstract (arXiv)

In this paper we investigate the problem of inducing a distribution over three-dimensional structures given two-dimensional views of multiple objects taken from unknown viewpoints. Our approach called "projective generative adversarial networks" (PrGANs) trains a deep generative model of 3D shapes whose projections match the distributions of the input 2D views. The addition of a projection module allows us to infer the underlying 3D shape distribution without using any 3D, viewpoint information, or annotation during the learning phase. We show that our approach produces 3D shapes of comparable quality to GANs trained on 3D data for a number of shape categories including chairs, airplanes, and cars. Experiments also show that the disentangled representation of 2D shapes into geometry and viewpoint leads to a good generative model of 2D shapes. The key advantage is that our model allows us to predict 3D, viewpoint, and generate novel views from an input image in a completely unsupervised manner.

Key facts. Cited by 121 papers in the map (data through 14 Oct 2026). First posted on arXiv 18 Dec 2016.

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Citing papers per year: 2021: 17; 2022: 36; 2023: 40; 2024: 18; 2025: 5; 2026: 5.

121 papers.

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  1. 2022Magic3D: High-Resolution Text-to-3D Content Creationcited by 1,290
  2. 2021Efficient Geometry-aware 3D Generative Adversarial Networkscited by 1,205
  3. 2021Common Objects in 3D: Large-Scale Learning and Evaluation of Real-life 3D Category Reconstructioncited by 652
  4. 2022GET3D: A Generative Model of High Quality 3D Textured Shapes Learned from Imagescited by 446
  5. 2023Instant3D: Fast Text-to-3D with Sparse-View Generation and Large Reconstruction Modelcited by 378
  6. 2023OmniObject3D: Large-Vocabulary 3D Object Dataset for Realistic Perception, Reconstruction and Generationcited by 326
  7. 2023ReconFusion: 3D Reconstruction with Diffusion Priorscited by 318
  8. 2023RealFusion: 360deg Reconstruction of Any Object from a Single Imagecited by 306
  9. 2021StyleSDF: High-Resolution 3D-Consistent Image and Geometry Generationcited by 289
  10. 20223D Neural Field Generation using Triplane Diffusioncited by 274
  11. 2023DreamAvatar: Text-and-Shape Guided 3D Human Avatar Generation via Diffusion Modelscited by 154
  12. 2023Let 2D Diffusion Model Know 3D-Consistency for Robust Text-to-3D Generationcited by 133
38 more
  1. 2022Next3D: Generative Neural Texture Rasterization for 3D-Aware Head Avatarscited by 124
  2. 2021FENeRF: Face Editing in Neural Radiance Fieldscited by 112
  3. 2022EpiGRAF: Rethinking training of 3D GANscited by 108
  4. 2023HoloDiffusion: Training a 3D Diffusion Model using 2D Imagescited by 106
  5. 2021Neural Parts: Learning Expressive 3D Shape Abstractions with Invertible Neural Networkscited by 103
  6. 2022Generative Neural Articulated Radiance Fieldscited by 101
  7. 2023Compositional 3D Scene Generation using Locally Conditioned Diffusioncited by 101
  8. 2024V3D: Video Diffusion Models are Effective 3D Generatorscited by 89
  9. 2023CityDreamer: Compositional Generative Model of Unbounded 3D Citiescited by 76
  10. 2023SceneDreamer: Unbounded 3D Scene Generation from 2D Image Collectionscited by 72
  11. 2021Unsupervised Learning of 3D Object Categories from Videos in the Wildcited by 67
  12. 2021Shelf-Supervised Mesh Prediction in the Wildcited by 65
  13. 2022Texturify: Generating Textures on 3D Shape Surfacescited by 65
  14. 2022Unsupervised Learning of Efficient Geometry-Aware Neural Articulated Representationscited by 65
  15. 2024Advances in 3D Generation: A Surveycited by 63
  16. 2022Generative Multiplane Images: Making a 2D GAN 3D-Awarecited by 57
  17. 2021CAMPARI: Camera-Aware Decomposed Generative Neural Radiance Fieldscited by 55
  18. 20223D GAN Inversion for Controllable Portrait Image Animationcited by 53
  19. 2023Instruct 3D-to-3D: Text Instruction Guided 3D-to-3D conversioncited by 48
  20. 2021FiG-NeRF: Figure-Ground Neural Radiance Fields for 3D Object Category Modellingcited by 47
  21. 2023DITTO-NeRF: Diffusion-based Iterative Text To Omni-directional 3D Modelcited by 43
  22. 2024Where Do We Stand with Implicit Neural Representations? A Technical and Performance Surveycited by 42
  23. 2022VoLux-GAN: A Generative Model for 3D Face Synthesis with HDRI Relightingcited by 37
  24. 2022Controllable 3D Face Synthesis with Conditional Generative Occupancy Fieldscited by 37
  25. 2021Learning Anchored Unsigned Distance Functions with Gradient Direction Alignment for Single-view Garment Reconstructioncited by 36
  26. 2023PartNeRF: Generating Part-Aware Editable 3D Shapes without 3D Supervisioncited by 36
  27. 2022HumanGen: Generating Human Radiance Fields with Explicit Priorscited by 33
  28. 2022DATID-3D: Diversity-Preserved Domain Adaptation Using Text-to-Image Diffusion for 3D Generative Modelcited by 32
  29. 2023HoloFusion: Towards Photo-realistic 3D Generative Modelingcited by 32
  30. 20213D-Aware Semantic-Guided Generative Model for Human Synthesiscited by 31
  31. 2024SphereHead: Stable 3D Full-head Synthesis with Spherical Tri-plane Representationcited by 30
  32. 2024Motion2VecSets: 4D Latent Vector Set Diffusion for Non-rigid Shape Reconstruction and Trackingcited by 29
  33. 2021Indoor Scene Generation from a Collection of Semantic-Segmented Depth Imagescited by 27
  34. 2021Unsupervised Learning of Fine Structure Generation for 3D Point Clouds by 2D Projection Matchingcited by 26
  35. 2021Differentiable Stereopsis: Meshes from multiple views using differentiable renderingcited by 26
  36. 2022Share With Thy Neighbors: Single-View Reconstruction by Cross-Instance Consistencycited by 26
  37. 2024Controllable Text-to-3D Generation via Surface-Aligned Gaussian Splattingcited by 26
  38. 2023GINA-3D: Learning to Generate Implicit Neural Assets in the Wildcited by 25

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