mlsanityData to 14 Oct 2026

NeRFs: The Search for the Best 3D Representation

arXiv 2308.02751 ↗First posted 5 Aug 2023cs.CV cs.AI cs.GRcited by 7

Not on the map. Why?

Abstract (arXiv)

Neural Radiance Fields or NeRFs have become the representation of choice for problems in view synthesis or image-based rendering, as well as in many other applications across computer graphics and vision, and beyond. At their core, NeRFs describe a new representation of 3D scenes or 3D geometry. Instead of meshes, disparity maps, multiplane images or even voxel grids, they represent the scene as a continuous volume, with volumetric parameters like view-dependent radiance and volume density obtained by querying a neural network. The NeRF representation has now been widely used, with thousands of papers extending or building on it every year, multiple authors and websites providing overviews and surveys, and numerous industrial applications and startup companies. In this article, we briefly review the NeRF representation, and describe the three decades-long quest to find the best 3D representation for view synthesis and related problems, culminating in the NeRF papers. We then describe new developments in terms of NeRF representations and make some observations and insights regarding the future of 3D representations.

Key facts. Cited by 7 papers in the map (data through 14 Oct 2026). Builds on 34 of its 84 references that are in the map. First posted on arXiv 5 Aug 2023.

Builds on

34 of 84 references.

References · 34

  1. 2014Fully Convolutional Networks for Semantic Segmentationcited by 4,859
  2. 2022Instant Neural Graphics Primitives with a Multiresolution Hash Encodingcited by 3,723
  3. 2022DreamFusion: Text-to-3D using 2D Diffusioncited by 3,025
  4. 2019DeepSDF: Learning Continuous Signed Distance Functions for Shape Representationcited by 2,689
  5. 2020Fourier Features Let Networks Learn High Frequency Functions in Low Dimensional Domainscited by 2,200
  6. 2021Mip-NeRF: A Multiscale Representation for Anti-Aliasing Neural Radiance Fieldscited by 1,964
  7. 2021Plenoxels: Radiance Fields without Neural Networkscited by 1,613
  8. 2018On the Spectral Bias of Neural Networkscited by 1,341
  9. 2022TensoRF: Tensorial Radiance Fieldscited by 1,280
  10. 2021Efficient Geometry-aware 3D Generative Adversarial Networkscited by 1,205
  11. 2019Scene Representation Networks: Continuous 3D-Structure-Aware Neural Scene Representationscited by 864
  12. 2020GIRAFFE: Representing Scenes as Compositional Generative Neural Feature Fieldscited by 785
22 more
  1. 2023K-Planes: Explicit Radiance Fields in Space, Time, and Appearancecited by 746
  2. 2021KiloNeRF: Speeding up Neural Radiance Fields with Thousands of Tiny MLPscited by 673
  3. 2019Local Light Field Fusion: Practical View Synthesis with Prescriptive Sampling Guidelinescited by 672
  4. 2021Common Objects in 3D: Large-Scale Learning and Evaluation of Real-life 3D Category Reconstructioncited by 652
  5. 2023Nerfstudio: A Modular Framework for Neural Radiance Field Developmentcited by 600
  6. 2021Ref-NeRF: Structured View-Dependent Appearance for Neural Radiance Fieldscited by 575
  7. 2022Point-NeRF: Point-based Neural Radiance Fieldscited by 503
  8. 2018DeepVoxels: Learning Persistent 3D Feature Embeddingscited by 405
  9. 2021Advances in Neural Renderingcited by 365
  10. 2022DynIBaR: Neural Dynamic Image-Based Renderingcited by 224
  11. 2020Neural Reflectance Fields for Appearance Acquisitioncited by 196
  12. 2015DeepStereo: Learning to Predict New Views from the World's Imagerycited by 185
  13. 2023HumanRF: High-Fidelity Neural Radiance Fields for Humans in Motioncited by 161
  14. 2016Learning-Based View Synthesis for Light Field Camerascited by 145
  15. 2020Deep Reflectance Volumes: Relightable Reconstructions from Multi-View Photometric Imagescited by 98
  16. 2023Real-Time Radiance Fields for Single-Image Portrait View Synthesiscited by 64
  17. 2020Neural Volume Rendering: NeRF And Beyondcited by 44
  18. 2022Approximate Differentiable Rendering with Algebraic Surfacescited by 44
  19. 2022A Level Set Theory for Neural Implicit Evolution under Explicit Flowscited by 42
  20. 2022Gravitationally Lensed Black Hole Emission Tomographycited by 22
  21. 2022NeAT: Neural Adaptive Tomographycited by 11
  22. 2023Neural Free-Viewpoint Relighting for Glossy Indirect Illuminationcited by 7

Built on by

Cited by year

Citing papers per year: 2023: 1; 2024: 4; 2025: 2.

7 papers.

  1. 2024VastGaussian: Vast 3D Gaussians for Large Scene Reconstructioncited by 209
  2. 2025MASH: Masked Anchored SpHerical Distances for 3D Shape Representation and Generationcited by 4
  3. 2023NeLF-Pro: Neural Light Field Probes for Multi-Scale Novel View Synthesiscited by 3
  4. 2025Uni-Render: A Unified Accelerator for Real-Time Rendering Across Diverse Neural Rendererscited by 2
  5. 2024Simple-RF: Regularizing Sparse Input Radiance Fields with Simpler Solutionscited by 1
  6. 2024Sampling for View Synthesis: From Local Light Field Fusion to Neural Radiance Fields and Beyondcited by 1
  7. 2024ActiveNeRF: Learning Accurate 3D Geometry by Active Pattern Projectioncited by 0