mlsanityData to 7 Oct 2026

GRF: Learning a General Radiance Field for 3D Representation and Rendering

arXiv 2010.04595 ↗First posted 9 Oct 2020cs.CV cs.AI cs.GRcited by 183

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Abstract (arXiv)

We present a simple yet powerful neural network that implicitly represents and renders 3D objects and scenes only from 2D observations. The network models 3D geometries as a general radiance field, which takes a set of 2D images with camera poses and intrinsics as input, constructs an internal representation for each point of the 3D space, and then renders the corresponding appearance and geometry of that point viewed from an arbitrary position. The key to our approach is to learn local features for each pixel in 2D images and to then project these features to 3D points, thus yielding general and rich point representations. We additionally integrate an attention mechanism to aggregate pixel features from multiple 2D views, such that visual occlusions are implicitly taken into account. Extensive experiments demonstrate that our method can generate high-quality and realistic novel views for novel objects, unseen categories and challenging real-world scenes.

Key facts. Cited by 183 papers in the map (data through 7 Oct 2026). First posted on arXiv 9 Oct 2020.

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2021: 10; 2022: 39; 2023: 71; 2024: 45; 2025: 14; 2026: 4.

183 papers.

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  1. 2023DreamGaussian: Generative Gaussian Splatting for Efficient 3D Content Creationcited by 837
  2. 2023pixelSplat: 3D Gaussian Splats from Image Pairs for Scalable Generalizable 3D Reconstructioncited by 668
  3. 2023One-2-3-45: Any Single Image to 3D Mesh in 45 Seconds without Per-Shape Optimizationcited by 555
  4. 2021Neural Fields in Visual Computing and Beyondcited by 539
  5. 2023DL3DV-10K: A Large-Scale Scene Dataset for Deep Learning-based 3D Visioncited by 514
  6. 2021Mega-NeRF: Scalable Construction of Large-Scale NeRFs for Virtual Fly-Throughscited by 396
  7. 2023Instant3D: Fast Text-to-3D with Sparse-View Generation and Large Reconstruction Modelcited by 376
  8. 2021Advances in Neural Renderingcited by 365
  9. 2023Make-It-3D: High-Fidelity 3D Creation from A Single Image with Diffusion Priorcited by 341
  10. 2023ReconFusion: 3D Reconstruction with Diffusion Priorscited by 317
  11. 2023One-2-3-45++: Fast Single Image to 3D Objects with Consistent Multi-View Generation and 3D Diffusioncited by 283
  12. 2022NoPe-NeRF: Optimising Neural Radiance Field with No Pose Priorcited by 235
38 more
  1. 2023MVImgNet: A Large-scale Dataset of Multi-view Imagescited by 219
  2. 2022SparseFusion: Distilling View-conditioned Diffusion for 3D Reconstructioncited by 216
  3. 2021GeoNeRF: Generalizing NeRF with Geometry Priorscited by 195
  4. 2022SPARF: Neural Radiance Fields from Sparse and Noisy Posescited by 195
  5. 2023DreamGaussian4D: Generative 4D Gaussian Splattingcited by 191
  6. 2023NerfDiff: Single-image View Synthesis with NeRF-guided Distillation from 3D-aware Diffusioncited by 179
  7. 2022SparseNeuS: Fast Generalizable Neural Surface Reconstruction from Sparse Viewscited by 175
  8. 2023GauHuman: Articulated Gaussian Splatting from Monocular Human Videoscited by 168
  9. 2022SinNeRF: Training Neural Radiance Fields on Complex Scenes from a Single Imagecited by 165
  10. 2022Fourier PlenOctrees for Dynamic Radiance Field Rendering in Real-timecited by 164
  11. 2022NeRF: Neural Radiance Field in 3D Vision: A Comprehensive Review (Updated Post-Gaussian Splatting)cited by 156
  12. 2022NeRDi: Single-View NeRF Synthesis with Language-Guided Diffusion as General Image Priorscited by 156
  13. 2022NeRFPlayer: A Streamable Dynamic Scene Representation with Decomposed Neural Radiance Fieldscited by 151
  14. 2021Efficient Neural Radiance Fields for Interactive Free-viewpoint Videocited by 150
  15. 2021Improving neural implicit surfaces geometry with patch warpingcited by 136
  16. 2022ActiveNeRF: Learning where to See with Uncertainty Estimationcited by 124
  17. 2022Generalizable Patch-Based Neural Renderingcited by 121
  18. 2023S-NeRF: Neural Radiance Fields for Street Viewscited by 116
  19. 2023Diffusion with Forward Models: Solving Stochastic Inverse Problems Without Direct Supervisioncited by 112
  20. 2023Learning to Render Novel Views from Wide-Baseline Stereo Pairscited by 103
  21. 2023GNFactor: Multi-Task Real Robot Learning with Generalizable Neural Feature Fieldscited by 99
  22. 2022Learning Dynamic Facial Radiance Fields for Few-Shot Talking Head Synthesiscited by 97
  23. 2021NeRF-SR: High-Quality Neural Radiance Fields using Supersamplingcited by 95
  24. 2024V3D: Video Diffusion Models are Effective 3D Generatorscited by 88
  25. 2022ViewFormer: NeRF-free Neural Rendering from Few Images Using Transformerscited by 70
  26. 2023Learning Neural Volumetric Representations of Dynamic Humans in Minutescited by 70
  27. 2022DM-NeRF: 3D Scene Geometry Decomposition and Manipulation from 2D Imagescited by 69
  28. 2023Forward Flow for Novel View Synthesis of Dynamic Scenescited by 67
  29. 2023ViVid-1-to-3: Novel View Synthesis with Video Diffusion Modelscited by 57
  30. 2023NeRF in the Palm of Your Hand: Corrective Augmentation for Robotics via Novel-View Synthesiscited by 56
  31. 2024MeshFormer: High-Quality Mesh Generation with 3D-Guided Reconstruction Modelcited by 55
  32. 2023NeO 360: Neural Fields for Sparse View Synthesis of Outdoor Scenescited by 53
  33. 2022MPS-NeRF: Generalizable 3D Human Rendering from Multiview Imagescited by 52
  34. 2022Self-supervised Neural Articulated Shape and Appearance Modelscited by 51
  35. 2022DiffDreamer: Towards Consistent Unsupervised Single-view Scene Extrapolation with Conditional Diffusion Modelscited by 51
  36. 2022IntrinsicNeRF: Learning Intrinsic Neural Radiance Fields for Editable Novel View Synthesiscited by 50
  37. 2023FeatureNeRF: Learning Generalizable NeRFs by Distilling Foundation Modelscited by 47
  38. 2024CViT: Continuous Vision Transformer for Operator Learningcited by 47

50 most cited of 183 All 183 (JSON)