mlsanityData to 7 Oct 2026

Space-time Neural Irradiance Fields for Free-Viewpoint Video

arXiv 2011.12950 ↗First posted 25 Nov 2020cs.CVcited by 414

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Abstract (arXiv)

We present a method that learns a spatiotemporal neural irradiance field for dynamic scenes from a single video. Our learned representation enables free-viewpoint rendering of the input video. Our method builds upon recent advances in implicit representations. Learning a spatiotemporal irradiance field from a single video poses significant challenges because the video contains only one observation of the scene at any point in time. The 3D geometry of a scene can be legitimately represented in numerous ways since varying geometry (motion) can be explained with varying appearance and vice versa. We address this ambiguity by constraining the time-varying geometry of our dynamic scene representation using the scene depth estimated from video depth estimation methods, aggregating contents from individual frames into a single global representation. We provide an extensive quantitative evaluation and demonstrate compelling free-viewpoint rendering results.

Key facts. Cited by 414 papers in the map (data through 7 Oct 2026). First posted on arXiv 25 Nov 2020.

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2021: 55; 2022: 89; 2023: 106; 2024: 90; 2025: 47; 2026: 27.

414 papers.

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  1. 2021Direct Voxel Grid Optimization: Super-fast Convergence for Radiance Fields Reconstructioncited by 961
  2. 2023Deformable 3D Gaussians for High-Fidelity Monocular Dynamic Scene Reconstructioncited by 753
  3. 2023K-Planes: Explicit Radiance Fields in Space, Time, and Appearancecited by 742
  4. 2021Depth-supervised NeRF: Fewer Views and Faster Training for Freecited by 732
  5. 2023Dynamic 3D Gaussians: Tracking by Persistent Dynamic View Synthesiscited by 731
  6. 2021KiloNeRF: Speeding up Neural Radiance Fields with Thousands of Tiny MLPscited by 672
  7. 2021BARF: Bundle-Adjusting Neural Radiance Fieldscited by 641
  8. 2023HexPlane: A Fast Representation for Dynamic Scenescited by 582
  9. 2021Neural Fields in Visual Computing and Beyondcited by 539
  10. 2021FastNeRF: High-Fidelity Neural Rendering at 200FPScited by 510
  11. 2022HumanNeRF: Free-viewpoint Rendering of Moving People from Monocular Videocited by 483
  12. 2021Dynamic View Synthesis from Dynamic Monocular Videocited by 420
38 more
  1. 2021Advances in Neural Renderingcited by 365
  2. 2022Fast Dynamic Radiance Fields with Time-Aware Neural Voxelscited by 344
  3. 2023Spacetime Gaussian Feature Splatting for Real-Time Dynamic View Synthesiscited by 341
  4. 2023SC-GS: Sparse-Controlled Gaussian Splatting for Editable Dynamic Scenescited by 339
  5. 2022NeuS2: Fast Learning of Neural Implicit Surfaces for Multi-view Reconstructioncited by 311
  6. 2023FreeNeRF: Improving Few-shot Neural Rendering with Free Frequency Regularizationcited by 310
  7. 2021StyleGAN-V: A Continuous Video Generator with the Price, Image Quality and Perks of StyleGAN2cited by 300
  8. 2021Mixture of Volumetric Primitives for Efficient Neural Renderingcited by 277
  9. 2023GaussianAvatars: Photorealistic Head Avatars with Rigged 3D Gaussianscited by 256
  10. 2023SparseNeRF: Distilling Depth Ranking for Few-shot Novel View Synthesiscited by 247
  11. 2024Shape of Motion: 4D Reconstruction from a Single Videocited by 247
  12. 2022NeuMan: Neural Human Radiance Field from a Single Videocited by 244
  13. 2022Panoptic Neural Fields: A Semantic Object-Aware Neural Scene Representationcited by 243
  14. 2021DONeRF: Towards Real-Time Rendering of Compact Neural Radiance Fields using Depth Oracle Networkscited by 232
  15. 2021I M Avatar: Implicit Morphable Head Avatars from Videoscited by 230
  16. 2021BungeeNeRF: Progressive Neural Radiance Field for Extreme Multi-scale Scene Renderingcited by 228
  17. 2022DynIBaR: Neural Dynamic Image-Based Renderingcited by 224
  18. 2021Editing Conditional Radiance Fieldscited by 222
  19. 2022Tensor4D : Efficient Neural 4D Decomposition for High-fidelity Dynamic Reconstruction and Renderingcited by 217
  20. 2022NeRF-Editing: Geometry Editing of Neural Radiance Fieldscited by 216
  21. 2024A Hierarchical 3D Gaussian Representation for Real-Time Rendering of Very Large Datasetscited by 214
  22. 2021HyperNeRF: A Higher-Dimensional Representation for Topologically Varying Neural Radiance Fieldscited by 210
  23. 2023Gaussian-Flow: 4D Reconstruction with Dynamic 3D Gaussian Particlecited by 210
  24. 2021Neural Descriptor Fields: SE(3)-Equivariant Object Representations for Manipulationcited by 204
  25. 2023Text-To-4D Dynamic Scene Generationcited by 204
  26. 2022Monocular Dynamic View Synthesis: A Reality Checkcited by 199
  27. 2023Robust Dynamic Radiance Fieldscited by 193
  28. 2021NerfingMVS: Guided Optimization of Neural Radiance Fields for Indoor Multi-view Stereocited by 191
  29. 2023DreamGaussian4D: Generative 4D Gaussian Splattingcited by 191
  30. 2021Stereo Radiance Fields (SRF): Learning View Synthesis for Sparse Views of Novel Scenescited by 190
  31. 2023Tracking Everything Everywhere All at Oncecited by 190
  32. 2022Generating Videos with Dynamics-aware Implicit Generative Adversarial Networkscited by 186
  33. 2024PhysDreamer: Physics-Based Interaction with 3D Objects via Video Generationcited by 185
  34. 2024MoSca: Dynamic Gaussian Fusion from Casual Videos via 4D Motion Scaffoldscited by 177
  35. 2021NEAT: Neural Attention Fields for End-to-End Autonomous Drivingcited by 174
  36. 2023HyperReel: High-Fidelity 6-DoF Video with Ray-Conditioned Samplingcited by 173
  37. 2022Fourier PlenOctrees for Dynamic Radiance Field Rendering in Real-timecited by 164
  38. 2024OmniRe: Omni Urban Scene Reconstructioncited by 159

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