mlsanityData to 7 Oct 2026

Dynamic NeRF: A Review

arXiv 2405.08609 ↗First posted 14 May 2024cs.CVcited by 5

Not on the map. Why?

Abstract (arXiv)

Neural Radiance Field(NeRF) is an novel implicit method to achieve the 3D reconstruction and representation with a high resolution. After the first research of NeRF is proposed, NeRF has gained a robust developing power and is booming in the 3D modeling, representation and reconstruction areas. However the first and most of the followed research projects based on NeRF is static, which are weak in the practical applications. Therefore, more researcher are interested and focused on the study of dynamic NeRF that is more feasible and useful in practical applications or situations. Compared with the static NeRF, implementing the Dynamic NeRF is more difficult and complex. But Dynamic is more potential in the future even is the basic of Editable NeRF. In this review, we made a detailed and abundant statement for the development and important implementation principles of Dynamci NeRF. The analysis of main principle and development of Dynamic NeRF is from 2021 to 2023, including the most of the Dynamic NeRF projects. What is more, with colorful and novel special designed figures and table, We also made a detailed comparison and analysis of different features of various of Dynamic. Besides, we analyzed and discussed the key methods to implement a Dynamic NeRF. The volume of the reference papers is large. The statements and comparisons are multidimensional. With a reading of this review, the whole development history and most of the main design method or principles of Dynamic NeRF can be easy understood and gained.

Key facts. Cited by 5 papers in the map (data through 7 Oct 2026). Builds on 55 of its 89 references that are in the map. First posted on arXiv 14 May 2024.

Builds on

55 of 89 references.

References · 55

  1. 20233D Gaussian Splatting for Real-Time Radiance Field Renderingcited by 6,141
  2. 2022Instant Neural Graphics Primitives with a Multiresolution Hash Encodingcited by 3,698
  3. 2021Mip-NeRF: A Multiscale Representation for Anti-Aliasing Neural Radiance Fieldscited by 1,957
  4. 2020D-NeRF: Neural Radiance Fields for Dynamic Scenescited by 1,459
  5. 2020Nerfies: Deformable Neural Radiance Fieldscited by 1,194
  6. 20234D Gaussian Splatting for Real-Time Dynamic Scene Renderingcited by 1,144
  7. 2021PlenOctrees for Real-time Rendering of Neural Radiance Fieldscited by 904
  8. 2020Neural Scene Flow Fields for Space-Time View Synthesis of Dynamic Scenescited by 750
  9. 2022Block-NeRF: Scalable Large Scene Neural View Synthesiscited by 720
  10. 2023HexPlane: A Fast Representation for Dynamic Scenescited by 582
  11. 2021Neural Fields in Visual Computing and Beyondcited by 539
  12. 2020Non-Rigid Neural Radiance Fields: Reconstruction and Novel View Synthesis of a Dynamic Scene From Monocular Videocited by 470
38 more
  1. 2021Dynamic View Synthesis from Dynamic Monocular Videocited by 420
  2. 2020Space-time Neural Irradiance Fields for Free-Viewpoint Videocited by 414
  3. 2021Animatable Neural Radiance Fields for Modeling Dynamic Human Bodiescited by 361
  4. 2022Fast Dynamic Radiance Fields with Time-Aware Neural Voxelscited by 344
  5. 2021NeRF in the Dark: High Dynamic Range View Synthesis from Noisy Raw Imagescited by 336
  6. 2022NeuS2: Fast Learning of Neural Implicit Surfaces for Multi-view Reconstructioncited by 311
  7. 2020Neural Scene Graphs for Dynamic Scenescited by 298
  8. 2022Tensor4D : Efficient Neural 4D Decomposition for High-fidelity Dynamic Reconstruction and Renderingcited by 217
  9. 2022Monocular Dynamic View Synthesis: A Reality Checkcited by 199
  10. 2021BANMo: Building Animatable 3D Neural Models from Many Casual Videoscited by 195
  11. 2022Fourier PlenOctrees for Dynamic Radiance Field Rendering in Real-timecited by 164
  12. 2021H-NeRF: Neural Radiance Fields for Rendering and Temporal Reconstruction of Humans in Motioncited by 157
  13. 2022Mixed Neural Voxels for Fast Multi-view Video Synthesiscited by 126
  14. 2021HumanNeRF: Efficiently Generated Human Radiance Field from Sparse Inputscited by 112
  15. 20213D Neural Scene Representations for Visuomotor Controlcited by 110
  16. 2022DeVRF: Fast Deformable Voxel Radiance Fields for Dynamic Scenescited by 103
  17. 2021T"oRF: Time-of-Flight Radiance Fields for Dynamic Scene View Synthesiscited by 88
  18. 2023Implicit Neural Representation in Medical Imaging: A Comparative Surveycited by 88
  19. 2023MonoHuman: Animatable Human Neural Field from Monocular Videocited by 85
  20. 2020Learning Compositional Radiance Fields of Dynamic Human Headscited by 78
  21. 2020STaR: Self-supervised Tracking and Reconstruction of Rigid Objects in Motion with Neural Renderingcited by 76
  22. 2022AvatarMAV: Fast 3D Head Avatar Reconstruction Using Motion-Aware Neural Voxelscited by 73
  23. 2022E-NeRF: Neural Radiance Fields from a Moving Event Cameracited by 70
  24. 2023Learning Neural Volumetric Representations of Dynamic Humans in Minutescited by 70
  25. 2022MonoNeRF: Learning a Generalizable Dynamic Radiance Field from Monocular Videoscited by 63
  26. 2017Transformation-Grounded Image Generation Network for Novel 3D View Synthesiscited by 59
  27. 2022Control-NeRF: Editable Feature Volumes for Scene Rendering and Manipulationcited by 57
  28. 2023Representing Volumetric Videos as Dynamic MLP Mapscited by 51
  29. 2022UV Volumes for Real-time Rendering of Editable Free-view Human Performancecited by 43
  30. 2022Neural Deformable Voxel Grid for Fast Optimization of Dynamic View Synthesiscited by 43
  31. 2022HDR-Plenoxels: Self-Calibrating High Dynamic Range Radiance Fieldscited by 40
  32. 2022FDNeRF: Few-shot Dynamic Neural Radiance Fields for Face Reconstruction and Expression Editingcited by 38
  33. 2021FLAME-in-NeRF : Neural control of Radiance Fields for Free View Face Animationcited by 33
  34. 2022EditableNeRF: Editing Topologically Varying Neural Radiance Fields by Key Pointscited by 30
  35. 2021HVH: Learning a Hybrid Neural Volumetric Representation for Dynamic Hair Performance Capturecited by 29
  36. 2022Common Pets in 3D: Dynamic New-View Synthesis of Real-Life Deformable Categoriescited by 29
  37. 2022NeRFInvertor: High Fidelity NeRF-GAN Inversion for Single-shot Real Image Animationcited by 23
  38. 2023Instant-NVR: Instant Neural Volumetric Rendering for Human-object Interactions from Monocular RGBD Streamcited by 23

50 most cited of 55 All 55 (JSON)

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2024: 2; 2025: 1; 2026: 2.

5 papers.

  1. 2025SpaceTimePilot: Generative Rendering of Dynamic Scenes Across Space and Timecited by 9
  2. 2024AI-Driven Innovations in Volumetric Video Streaming: A Reviewcited by 2
  3. 2024Editing Implicit and Explicit Representations of Radiance Fields: A Surveycited by 1
  4. 2026Node-RF: Learning Generalized Continuous Space-Time Scene Dynamics with Neural ODE-based NeRFscited by 0
  5. 2026AnchorSplat: Fast and Structure Consistent Detail Synthesis for Gaussian Splattingcited by 0