mlsanityData to 7 Oct 2026

UNISURF: Unifying Neural Implicit Surfaces and Radiance Fields for Multi-View Reconstruction

arXiv 2104.10078 ↗First posted 20 Apr 2021cs.CVcited by 643

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Abstract (arXiv)

Neural implicit 3D representations have emerged as a powerful paradigm for reconstructing surfaces from multi-view images and synthesizing novel views. Unfortunately, existing methods such as DVR or IDR require accurate per-pixel object masks as supervision. At the same time, neural radiance fields have revolutionized novel view synthesis. However, NeRF's estimated volume density does not admit accurate surface reconstruction. Our key insight is that implicit surface models and radiance fields can be formulated in a unified way, enabling both surface and volume rendering using the same model. This unified perspective enables novel, more efficient sampling procedures and the ability to reconstruct accurate surfaces without input masks. We compare our method on the DTU, BlendedMVS, and a synthetic indoor dataset. Our experiments demonstrate that we outperform NeRF in terms of reconstruction quality while performing on par with IDR without requiring masks.

Key facts. Cited by 643 papers in the map (data through 7 Oct 2026). Builds on 37 of its 67 references that are in the map. First posted on arXiv 20 Apr 2021.

Builds on

37 of 67 references.

References · 37

  1. 2018Encoder-Decoder with Atrous Separable Convolution for Semantic Image Segmentationcited by 3,210
  2. 2019DeepSDF: Learning Continuous Signed Distance Functions for Shape Representationcited by 2,682
  3. 2018Occupancy Networks: Learning 3D Reconstruction in Function Spacecited by 2,037
  4. 2020D-NeRF: Neural Radiance Fields for Dynamic Scenescited by 1,459
  5. 2020NeRF in the Wild: Neural Radiance Fields for Unconstrained Photo Collectionscited by 1,230
  6. 2020Neural Sparse Voxel Fieldscited by 959
  7. 2019Scene Representation Networks: Continuous 3D-Structure-Aware Neural Scene Representationscited by 864
  8. 2020NeRF++: Analyzing and Improving Neural Radiance Fieldscited by 857
  9. 2019PIFu: Pixel-Aligned Implicit Function for High-Resolution Clothed Human Digitizationcited by 818
  10. 2020GIRAFFE: Representing Scenes as Compositional Generative Neural Feature Fieldscited by 784
  11. 2018MVSNet: Depth Inference for Unstructured Multi-view Stereocited by 780
  12. 2020Convolutional Occupancy Networkscited by 760
25 more
  1. 2020Implicit Geometric Regularization for Learning Shapescited by 707
  2. 2019Differentiable Volumetric Rendering: Learning Implicit 3D Representations without 3D Supervisioncited by 699
  3. 2020GRAF: Generative Radiance Fields for 3D-Aware Image Synthesiscited by 688
  4. 2019Local Light Field Fusion: Practical View Synthesis with Prescriptive Sampling Guidelinescited by 672
  5. 2020Neural Body: Implicit Neural Representations with Structured Latent Codes for Novel View Synthesis of Dynamic Humanscited by 634
  6. 2020NeRV: Neural Reflectance and Visibility Fields for Relighting and View Synthesiscited by 493
  7. 2019BlendedMVS: A Large-scale Dataset for Generalized Multi-view Stereo Networkscited by 487
  8. 2020NeRD: Neural Reflectance Decomposition from Image Collectionscited by 446
  9. 2019DISN: Deep Implicit Surface Network for High-quality Single-view 3D Reconstructioncited by 332
  10. 2018DeepMVS: Learning Multi-view Stereopsiscited by 277
  11. 2019Recurrent MVSNet for High-resolution Multi-view Stereo Depth Inferencecited by 252
  12. 2019Learning Shape Templates with Structured Implicit Functionscited by 242
  13. 2019Texture Fields: Learning Texture Representations in Function Spacecited by 210
  14. 2016DeMoN: Depth and Motion Network for Learning Monocular Stereocited by 200
  15. 2019DIST: Rendering Deep Implicit Signed Distance Function with Differentiable Sphere Tracingcited by 179
  16. 2017Multi-view Supervision for Single-view Reconstruction via Differentiable Ray Consistencycited by 177
  17. 2015Learning to Compare Image Patches via Convolutional Neural Networkscited by 109
  18. 2021Neural Lumigraph Renderingcited by 105
  19. 2019Learning to Infer Implicit Surfaces without 3D Supervisioncited by 103
  20. 2019Controlling Neural Level Setscited by 76
  21. 2017OctNetFusion: Learning Depth Fusion from Datacited by 45
  22. 2019RayNet: Learning Volumetric 3D Reconstruction with Ray Potentialscited by 26
  23. 2017Learned Multi-Patch Similaritycited by 24
  24. 2020Learning Implicit Surface Light Fieldscited by 23
  25. 2020Multiview Neural Surface Reconstruction by Disentangling Geometry and Appearancecited by 9

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2021: 36; 2022: 136; 2023: 211; 2024: 153; 2025: 73; 2026: 34.

643 papers.

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  1. 2021Mip-NeRF 360: Unbounded Anti-Aliased Neural Radiance Fieldscited by 2,013
  2. 2021NeuS: Learning Neural Implicit Surfaces by Volume Rendering for Multi-view Reconstructioncited by 1,701
  3. 2023DUSt3R: Geometric 3D Vision Made Easycited by 1,526
  4. 2022TensoRF: Tensorial Radiance Fieldscited by 1,275
  5. 2021Efficient Geometry-aware 3D Generative Adversarial Networkscited by 1,204
  6. 20242D Gaussian Splatting for Geometrically Accurate Radiance Fieldscited by 1,061
  7. 2021Volume Rendering of Neural Implicit Surfacescited by 990
  8. 2021Direct Voxel Grid Optimization: Super-fast Convergence for Radiance Fields Reconstructioncited by 961
  9. 2023Scaffold-GS: Structured 3D Gaussians for View-Adaptive Renderingcited by 684
  10. 2021RegNeRF: Regularizing Neural Radiance Fields for View Synthesis from Sparse Inputscited by 614
  11. 2023SuGaR: Surface-Aligned Gaussian Splatting for Efficient 3D Mesh Reconstruction and High-Quality Mesh Renderingcited by 611
  12. 2022Score Jacobian Chaining: Lifting Pretrained 2D Diffusion Models for 3D Generationcited by 597
38 more
  1. 2023Nerfstudio: A Modular Framework for Neural Radiance Field Developmentcited by 596
  2. 2021NICE-SLAM: Neural Implicit Scalable Encoding for SLAMcited by 586
  3. 2021Ref-NeRF: Structured View-Dependent Appearance for Neural Radiance Fieldscited by 569
  4. 2021Neural Fields in Visual Computing and Beyondcited by 539
  5. 2022MonoSDF: Exploring Monocular Geometric Cues for Neural Implicit Surface Reconstructioncited by 467
  6. 2023Neuralangelo: High-Fidelity Neural Surface Reconstructioncited by 464
  7. 2021Advances in Neural Renderingcited by 365
  8. 2021Extracting Triangular 3D Models, Materials, and Lighting From Imagescited by 363
  9. 2023OmniObject3D: Large-Vocabulary 3D Object Dataset for Realistic Perception, Reconstruction and Generationcited by 324
  10. 2022NeuS2: Fast Learning of Neural Implicit Surfaces for Multi-view Reconstructioncited by 311
  11. 20223D Neural Field Generation using Triplane Diffusioncited by 274
  12. 2021Urban Radiance Fieldscited by 263
  13. 2023SparseNeRF: Distilling Depth Ranking for Few-shot Novel View Synthesiscited by 247
  14. 2022NoPe-NeRF: Optimising Neural Radiance Field with No Pose Priorcited by 235
  15. 2024Gaussian Opacity Fields: Efficient Adaptive Surface Reconstruction in Unbounded Scenescited by 226
  16. 2023BakedSDF: Meshing Neural SDFs for Real-Time View Synthesiscited by 220
  17. 2022Tensor4D : Efficient Neural 4D Decomposition for High-fidelity Dynamic Reconstruction and Renderingcited by 217
  18. 2021GRAM: Generative Radiance Manifolds for 3D-Aware Image Generationcited by 216
  19. 2022Geo-Neus: Geometry-Consistent Neural Implicit Surfaces Learning for Multi-view Reconstructioncited by 211
  20. 2021GeoNeRF: Generalizing NeRF with Geometry Priorscited by 195
  21. 20233DGS-Avatar: Animatable Avatars via Deformable 3D Gaussian Splattingcited by 195
  22. 2022NeRF-SLAM: Real-Time Dense Monocular SLAM with Neural Radiance Fieldscited by 188
  23. 2021Shape As Points: A Differentiable Poisson Solvercited by 186
  24. 2022SparseNeuS: Fast Generalizable Neural Surface Reconstruction from Sparse Viewscited by 175
  25. 2024VR-GS: A Physical Dynamics-Aware Interactive Gaussian Splatting System in Virtual Realitycited by 175
  26. 2022Panoptic Lifting for 3D Scene Understanding with Neural Fieldscited by 171
  27. 2022Shape, Light, and Material Decomposition from Images using Monte Carlo Rendering and Denoisingcited by 163
  28. 2023NeRO: Neural Geometry and BRDF Reconstruction of Reflective Objects from Multiview Imagescited by 163
  29. 2023NICER-SLAM: Neural Implicit Scene Encoding for RGB SLAMcited by 162
  30. 2023Point-SLAM: Dense Neural Point Cloud-based SLAMcited by 160
  31. 2024High-quality Surface Reconstruction using Gaussian Surfelscited by 159
  32. 2022ESLAM: Efficient Dense SLAM System Based on Hybrid Representation of Signed Distance Fieldscited by 158
  33. 2021H-NeRF: Neural Radiance Fields for Rendering and Temporal Reconstruction of Humans in Motioncited by 157
  34. 2022NeRF: Neural Radiance Field in 3D Vision: A Comprehensive Review (Updated Post-Gaussian Splatting)cited by 156
  35. 2022Panoptic NeRF: 3D-to-2D Label Transfer for Panoptic Urban Scene Segmentationcited by 152
  36. 2023Gaussian-SLAM: Photo-realistic Dense SLAM with Gaussian Splattingcited by 152
  37. 2021Efficient Neural Radiance Fields for Interactive Free-viewpoint Videocited by 150
  38. 2022Vox-Fusion: Dense Tracking and Mapping with Voxel-based Neural Implicit Representationcited by 149

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