mlsanityData to 14 Oct 2026

CodeNeRF: Disentangled Neural Radiance Fields for Object Categories

arXiv 2109.01750 ↗First posted 3 Sep 2021cs.GR cs.CV cs.LGcited by 183

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

Abstract (arXiv)

CodeNeRF is an implicit 3D neural representation that learns the variation of object shapes and textures across a category and can be trained, from a set of posed images, to synthesize novel views of unseen objects. Unlike the original NeRF, which is scene specific, CodeNeRF learns to disentangle shape and texture by learning separate embeddings. At test time, given a single unposed image of an unseen object, CodeNeRF jointly estimates camera viewpoint, and shape and appearance codes via optimization. Unseen objects can be reconstructed from a single image, and then rendered from new viewpoints or their shape and texture edited by varying the latent codes. We conduct experiments on the SRN benchmark, which show that CodeNeRF generalises well to unseen objects and achieves on-par performance with methods that require known camera pose at test time. Our results on real-world images demonstrate that CodeNeRF can bridge the sim-to-real gap. Project page: urlhttps://github.com/wayne1123/code-nerf

Key facts. Cited by 183 papers in the map (data through 14 Oct 2026). Builds on 24 of its 37 references that are in the map. First posted on arXiv 3 Sep 2021.

Builds on

24 of 37 references.

References · 24

  1. 2016PointNet: Deep Learning on Point Sets for 3D Classification and Segmentationcited by 5,248
  2. 2015ShapeNet: An Information-Rich 3D Model Repositorycited by 2,897
  3. 2019DeepSDF: Learning Continuous Signed Distance Functions for Shape Representationcited by 2,689
  4. 2018Occupancy Networks: Learning 3D Reconstruction in Function Spacecited by 2,041
  5. 2020pixelNeRF: Neural Radiance Fields from One or Few Imagescited by 1,584
  6. 2018Learning Implicit Fields for Generative Shape Modelingcited by 1,060
  7. 2019Scene Representation Networks: Continuous 3D-Structure-Aware Neural Scene Representationscited by 864
  8. 2020Accelerating 3D Deep Learning with PyTorch3Dcited by 784
  9. 2019Differentiable Volumetric Rendering: Learning Implicit 3D Representations without 3D Supervisioncited by 700
  10. 2020GRAF: Generative Radiance Fields for 3D-Aware Image Synthesiscited by 689
  11. 2018Pixel2Mesh: Generating 3D Mesh Models from Single RGB Imagescited by 651
  12. 20163D-R2N2: A Unified Approach for Single and Multi-view 3D Object Reconstructioncited by 588
12 more
  1. 2016Learning a Probabilistic Latent Space of Object Shapes via 3D Generative-Adversarial Modelingcited by 558
  2. 2018AtlasNet: A Papier-Mach'e Approach to Learning 3D Surface Generationcited by 539
  3. 2017Neural 3D Mesh Renderercited by 437
  4. 2018DeepVoxels: Learning Persistent 3D Feature Embeddingscited by 405
  5. 2020INeRF: Inverting Neural Radiance Fields for Pose Estimationcited by 382
  6. 2019DISN: Deep Implicit Surface Network for High-quality Single-view 3D Reconstructioncited by 333
  7. 2019What Do Single-view 3D Reconstruction Networks Learn?cited by 260
  8. 2018Pix3D: Dataset and Methods for Single-Image 3D Shape Modelingcited by 218
  9. 2020MeshSDF: Differentiable Iso-Surface Extractioncited by 112
  10. 2020FroDO: From Detections to 3D Objectscited by 51
  11. 2020Equivariant Neural Renderingcited by 48
  12. 2019Photometric Mesh Optimization for Video-Aligned 3D Object Reconstructioncited by 28

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Cited by year (2026 to 14 Oct)

Citing papers per year: 2021: 11; 2022: 46; 2023: 70; 2024: 40; 2025: 10; 2026: 6.

183 papers.

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  1. 2023LRM: Large Reconstruction Model for Single Image to 3Dcited by 849
  2. 2021RegNeRF: Regularizing Neural Radiance Fields for View Synthesis from Sparse Inputscited by 615
  3. 2023One-2-3-45: Any Single Image to 3D Mesh in 45 Seconds without Per-Shape Optimizationcited by 560
  4. 2021Neural Fields in Visual Computing and Beyondcited by 540
  5. 2022Decomposing NeRF for Editing via Feature Field Distillationcited by 371
  6. 2021CLIP-NeRF: Text-and-Image Driven Manipulation of Neural Radiance Fieldscited by 370
  7. 2021Advances in Neural Renderingcited by 365
  8. 2023Splatter Image: Ultra-Fast Single-View 3D Reconstructioncited by 364
  9. 2023RealFusion: 360deg Reconstruction of Any Object from a Single Imagecited by 306
  10. 2022Novel View Synthesis with Diffusion Modelscited by 300
  11. 20243D Reconstruction with Spatial Memorycited by 277
  12. 2023Generative Novel View Synthesis with 3D-Aware Diffusion Modelscited by 274
38 more
  1. 2021Urban Radiance Fieldscited by 263
  2. 2022Panoptic Neural Fields: A Semantic Object-Aware Neural Scene Representationcited by 243
  3. 2021Scene Representation Transformer: Geometry-Free Novel View Synthesis Through Set-Latent Scene Representationscited by 227
  4. 2022Tensor4D : Efficient Neural 4D Decomposition for High-fidelity Dynamic Reconstruction and Renderingcited by 217
  5. 2023NerfDiff: Single-image View Synthesis with NeRF-guided Distillation from 3D-aware Diffusioncited by 180
  6. 2023Single-Stage Diffusion NeRF: A Unified Approach to 3D Generation and Reconstructioncited by 180
  7. 2023GauHuman: Articulated Gaussian Splatting from Monocular Human Videoscited by 168
  8. 2022NeRF: Neural Radiance Field in 3D Vision: A Comprehensive Review (Updated Post-Gaussian Splatting)cited by 158
  9. 2021CIPS-3D: A 3D-Aware Generator of GANs Based on Conditionally-Independent Pixel Synthesiscited by 149
  10. 2021NeSF: Neural Semantic Fields for Generalizable Semantic Segmentation of 3D Scenescited by 119
  11. 2024latentSplat: Autoencoding Variational Gaussians for Fast Generalizable 3D Reconstructioncited by 118
  12. 2023Viewset Diffusion: (0-)Image-Conditioned 3D Generative Models from 2D Datacited by 113
  13. 2022MagicPony: Learning Articulated 3D Animals in the Wildcited by 112
  14. 2022Vision Transformer for NeRF-Based View Synthesis from a Single Input Imagecited by 104
  15. 2023GNFactor: Multi-Task Real Robot Learning with Generalizable Neural Feature Fieldscited by 99
  16. 2021NeRF-SR: High-Quality Neural Radiance Fields using Supersamplingcited by 95
  17. 2023SINE: Semantic-driven Image-based NeRF Editing with Prior-guided Editing Fieldcited by 94
  18. 2024LN3DIFF++: Scalable Latent Neural Fields Diffusion for Speedy 3D Generationcited by 92
  19. 2022Object Scene Representation Transformercited by 90
  20. 2023SHERF: Generalizable Human NeRF from a Single Imagecited by 88
  21. 2021LOLNeRF: Learn from One Lookcited by 84
  22. 2023PC2: Projection-Conditioned Point Cloud Diffusion for Single-Image 3D Reconstructioncited by 84
  23. 2023Consistent123: Improve Consistency for One Image to 3D Object Synthesiscited by 84
  24. 2022InfiniteNature-Zero: Learning Perpetual View Generation of Natural Scenes from Single Imagescited by 82
  25. 2022Pix2NeRF: Unsupervised Conditional π-GAN for Single Image to Neural Radiance Fields Translationcited by 73
  26. 2022GRAM-HD: 3D-Consistent Image Generation at High Resolution with Generative Radiance Manifoldscited by 73
  27. 2025Pow3R: Empowering Unconstrained 3D Reconstruction with Camera and Scene Priorscited by 72
  28. 2022NeRF-SOS: Any-View Self-supervised Object Segmentation on Complex Scenescited by 71
  29. 2022DM-NeRF: 3D Scene Geometry Decomposition and Manipulation from 2D Imagescited by 69
  30. 2023vMAP: Vectorised Object Mapping for Neural Field SLAMcited by 67
  31. 2021CoNeRF: Controllable Neural Radiance Fieldscited by 65
  32. 2023Real-Time Radiance Fields for Single-Image Portrait View Synthesiscited by 64
  33. 2022MonoNeRF: Learning a Generalizable Dynamic Radiance Field from Monocular Videoscited by 63
  34. 2024PartGen: Part-level 3D Generation and Reconstruction with Multi-View Diffusion Modelscited by 62
  35. 2022AutoRF: Learning 3D Object Radiance Fields from Single View Observationscited by 59
  36. 2022SparsePose: Sparse-View Camera Pose Regression and Refinementcited by 53
  37. 2023NeO 360: Neural Fields for Sparse View Synthesis of Outdoor Scenescited by 53
  38. 2022DiffDreamer: Towards Consistent Unsupervised Single-view Scene Extrapolation with Conditional Diffusion Modelscited by 51

50 most cited of 183 All 183 (JSON)