mlsanityData to 14 Oct 2026

pixelNeRF: Neural Radiance Fields from One or Few Images

arXiv 2012.02190 ↗First posted 3 Dec 2020cs.CV cs.GR cs.LGcited by 1,584

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Cited by 152 in Diffusion models, but placed by its own abstract, which didn’t fit.

Abstract (arXiv)

We propose pixelNeRF, a learning framework that predicts a continuous neural scene representation conditioned on one or few input images. The existing approach for constructing neural radiance fields involves optimizing the representation to every scene independently, requiring many calibrated views and significant compute time. We take a step towards resolving these shortcomings by introducing an architecture that conditions a NeRF on image inputs in a fully convolutional manner. This allows the network to be trained across multiple scenes to learn a scene prior, enabling it to perform novel view synthesis in a feed-forward manner from a sparse set of views (as few as one). Leveraging the volume rendering approach of NeRF, our model can be trained directly from images with no explicit 3D supervision. We conduct extensive experiments on ShapeNet benchmarks for single image novel view synthesis tasks with held-out objects as well as entire unseen categories. We further demonstrate the flexibility of pixelNeRF by demonstrating it on multi-object ShapeNet scenes and real scenes from the DTU dataset. In all cases, pixelNeRF outperforms current state-of-the-art baselines for novel view synthesis and single image 3D reconstruction. For the video and code, please visit the project website: https://alexyu.net/pixelnerf

Key facts. Cited by 1,584 papers in the map (data through 14 Oct 2026). First posted on arXiv 3 Dec 2020.

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Cited by year (2026 to 14 Oct)

Citing papers per year: 2021: 106; 2022: 234; 2023: 411; 2024: 420; 2025: 255; 2026: 158.

1,584 papers.

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  1. 2023Zero-1-to-3: Zero-shot One Image to 3D Objectcited by 1,489
  2. 2022TensoRF: Tensorial Radiance Fieldscited by 1,280
  3. 2021Direct Voxel Grid Optimization: Super-fast Convergence for Radiance Fields Reconstructioncited by 964
  4. 2021PlenOctrees for Real-time Rendering of Neural Radiance Fieldscited by 905
  5. 2023LRM: Large Reconstruction Model for Single Image to 3Dcited by 849
  6. 2023DreamGaussian: Generative Gaussian Splatting for Efficient 3D Content Creationcited by 843
  7. 2023Objaverse-XL: A Universe of 10M+ 3D Objectscited by 774
  8. 2023ScanNet++: A High-Fidelity Dataset of 3D Indoor Scenescited by 764
  9. 2021MVSNeRF: Fast Generalizable Radiance Field Reconstruction from Multi-View Stereocited by 740
  10. 2021Depth-supervised NeRF: Fewer Views and Faster Training for Freecited by 735
  11. 2021IBRNet: Learning Multi-View Image-Based Renderingcited by 703
  12. 2022Point-E: A System for Generating 3D Point Clouds from Complex Promptscited by 699
38 more
  1. 2025Depth Anything 3: Recovering the Visual Space from Any Viewscited by 692
  2. 2023pixelSplat: 3D Gaussian Splats from Image Pairs for Scalable Generalizable 3D Reconstructioncited by 684
  3. 2021KiloNeRF: Speeding up Neural Radiance Fields with Thousands of Tiny MLPscited by 673
  4. 2021Common Objects in 3D: Large-Scale Learning and Evaluation of Real-life 3D Category Reconstructioncited by 652
  5. 2021BARF: Bundle-Adjusting Neural Radiance Fieldscited by 642
  6. 2021RegNeRF: Regularizing Neural Radiance Fields for View Synthesis from Sparse Inputscited by 615
  7. 2023Nerfstudio: A Modular Framework for Neural Radiance Field Developmentcited by 600
  8. 2023HexPlane: A Fast Representation for Dynamic Scenescited by 587
  9. 2024MVSplat: Efficient 3D Gaussian Splatting from Sparse Multi-View Imagescited by 566
  10. 2023One-2-3-45: Any Single Image to 3D Mesh in 45 Seconds without Per-Shape Optimizationcited by 560
  11. 2025Continuous 3D Perception Model with Persistent Statecited by 548
  12. 2021Neural Fields in Visual Computing and Beyondcited by 540
  13. 2023DL3DV-10K: A Large-Scale Scene Dataset for Deep Learning-based 3D Visioncited by 537
  14. 2022Point-NeRF: Point-based Neural Radiance Fieldscited by 503
  15. 2022MonoSDF: Exploring Monocular Geometric Cues for Neural Implicit Surface Reconstructioncited by 470
  16. 2021Putting NeRF on a Diet: Semantically Consistent Few-Shot View Synthesiscited by 464
  17. 2024CAT3D: Create Anything in 3D with Multi-View Diffusion Modelscited by 432
  18. 2023LangSplat: 3D Language Gaussian Splattingcited by 415
  19. 2024ViewCrafter: Taming Video Diffusion Models for High-fidelity Novel View Synthesiscited by 403
  20. 2021Mega-NeRF: Scalable Construction of Large-Scale NeRFs for Virtual Fly-Throughscited by 398
  21. 2023Magic123: One Image to High-Quality 3D Object Generation Using Both 2D and 3D Diffusion Priorscited by 397
  22. 2022Kubric: A scalable dataset generatorcited by 381
  23. 2023Instant3D: Fast Text-to-3D with Sparse-View Generation and Large Reconstruction Modelcited by 378
  24. 2023Compact 3D Gaussian Representation for Radiance Fieldcited by 372
  25. 2021Advances in Neural Renderingcited by 365
  26. 2023Feature 3DGS: Supercharging 3D Gaussian Splatting to Enable Distilled Feature Fieldscited by 364
  27. 2023Splatter Image: Ultra-Fast Single-View 3D Reconstructioncited by 364
  28. 2024GS-LRM: Large Reconstruction Model for 3D Gaussian Splattingcited by 349
  29. 2022Fast Dynamic Radiance Fields with Time-Aware Neural Voxelscited by 346
  30. 2023Make-It-3D: High-Fidelity 3D Creation from A Single Image with Diffusion Priorcited by 343
  31. 2025GEN3C: 3D-Informed World-Consistent Video Generation with Precise Camera Controlcited by 341
  32. 2021Text2Mesh: Text-Driven Neural Stylization for Meshescited by 334
  33. 2021Light Field Networks: Neural Scene Representations with Single-Evaluation Renderingcited by 332
  34. 2023OmniObject3D: Large-Vocabulary 3D Object Dataset for Realistic Perception, Reconstruction and Generationcited by 326
  35. 2023ReconFusion: 3D Reconstruction with Diffusion Priorscited by 318
  36. 2021Neural RGB-D Surface Reconstructioncited by 313
  37. 2023FreeNeRF: Improving Few-shot Neural Rendering with Free Frequency Regularizationcited by 311
  38. 2023RealFusion: 360deg Reconstruction of Any Object from a Single Imagecited by 306

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