mlsanityData to 7 Oct 2026

ProvNeRF: Modeling per Point Provenance in NeRFs as a Stochastic Field

arXiv 2401.08140 ↗First posted 16 Jan 2024cs.CVcited by 3

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Abstract (arXiv)

Neural radiance fields (NeRFs) have gained popularity with multiple works showing promising results across various applications. However, to the best of our knowledge, existing works do not explicitly model the distribution of training camera poses, or consequently the triangulation quality, a key factor affecting reconstruction quality dating back to classical vision literature. We close this gap with ProvNeRF, an approach that models the provenance for each point -- i.e., the locations where it is likely visible -- of NeRFs as a stochastic field. We achieve this by extending implicit maximum likelihood estimation (IMLE) to functional space with an optimizable objective. We show that modeling per-point provenance during the NeRF optimization enriches the model with information on triangulation leading to improvements in novel view synthesis and uncertainty estimation under the challenging sparse, unconstrained view setting against competitive baselines.

Key facts. Cited by 3 papers in the map (data through 7 Oct 2026). Builds on 54 of its 71 references that are in the map. First posted on arXiv 16 Jan 2024.

Builds on

54 of 71 references.

References · 54

  1. 2018The Unreasonable Effectiveness of Deep Features as a Perceptual Metriccited by 11,029
  2. 20233D Gaussian Splatting for Real-Time Radiance Field Renderingcited by 6,141
  3. 2017ScanNet: Richly-annotated 3D Reconstructions of Indoor Scenescited by 3,088
  4. 2021Mip-NeRF 360: Unbounded Anti-Aliased Neural Radiance Fieldscited by 2,013
  5. 2021Mip-NeRF: A Multiscale Representation for Anti-Aliasing Neural Radiance Fieldscited by 1,957
  6. 2020pixelNeRF: Neural Radiance Fields from One or Few Imagescited by 1,574
  7. 2017Matterport3D: Learning from RGB-D Data in Indoor Environmentscited by 1,354
  8. 2020NeRF in the Wild: Neural Radiance Fields for Unconstrained Photo Collectionscited by 1,230
  9. 2020Nerfies: Deformable Neural Radiance Fieldscited by 1,194
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  11. 2021MVSNeRF: Fast Generalizable Radiance Field Reconstruction from Multi-View Stereocited by 735
  12. 2021Depth-supervised NeRF: Fewer Views and Faster Training for Freecited by 732
38 more
  1. 2022Block-NeRF: Scalable Large Scene Neural View Synthesiscited by 720
  2. 2021IBRNet: Learning Multi-View Image-Based Renderingcited by 698
  3. 2023pixelSplat: 3D Gaussian Splats from Image Pairs for Scalable Generalizable 3D Reconstructioncited by 668
  4. 2023Zip-NeRF: Anti-Aliased Grid-Based Neural Radiance Fieldscited by 667
  5. 2021RegNeRF: Regularizing Neural Radiance Fields for View Synthesis from Sparse Inputscited by 614
  6. 2023Nerfstudio: A Modular Framework for Neural Radiance Field Developmentcited by 596
  7. 2021Ref-NeRF: Structured View-Dependent Appearance for Neural Radiance Fieldscited by 569
  8. 2023LERF: Language Embedded Radiance Fieldscited by 538
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  10. 2022MonoSDF: Exploring Monocular Geometric Cues for Neural Implicit Surface Reconstructioncited by 467
  11. 2021Putting NeRF on a Diet: Semantically Consistent Few-Shot View Synthesiscited by 464
  12. 2021In-Place Scene Labelling and Understanding with Implicit Scene Representationcited by 411
  13. 2022Decomposing NeRF for Editing via Feature Field Distillationcited by 370
  14. 2023SC-GS: Sparse-Controlled Gaussian Splatting for Editable Dynamic Scenescited by 339
  15. 2023FreeNeRF: Improving Few-shot Neural Rendering with Free Frequency Regularizationcited by 310
  16. 2021Dense Depth Priors for Neural Radiance Fields from Sparse Input Viewscited by 301
  17. 2021BungeeNeRF: Progressive Neural Radiance Field for Extreme Multi-scale Scene Renderingcited by 228
  18. 2022DynIBaR: Neural Dynamic Image-Based Renderingcited by 224
  19. 2022NeRF-Editing: Geometry Editing of Neural Radiance Fieldscited by 216
  20. 2020Neural Reflectance Fields for Appearance Acquisitioncited by 196
  21. 2021NerfingMVS: Guided Optimization of Neural Radiance Fields for Indoor Multi-view Stereocited by 191
  22. 2021CodeNeRF: Disentangled Neural Radiance Fields for Object Categoriescited by 183
  23. 2021Vision-Only Robot Navigation in a Neural Radiance Worldcited by 153
  24. 2022ActiveNeRF: Learning where to See with Uncertainty Estimationcited by 124
  25. 2021Dex-NeRF: Using a Neural Radiance Field to Grasp Transparent Objectscited by 119
  26. 2023Learning to Render Novel Views from Wide-Baseline Stereo Pairscited by 103
  27. 2023Bayes' Rays: Uncertainty Quantification for Neural Radiance Fieldscited by 90
  28. 2021Stochastic Neural Radiance Fields: Quantifying Uncertainty in Implicit 3D Representationscited by 80
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  30. 2022Conditional-Flow NeRF: Accurate 3D Modelling with Reliable Uncertainty Quantificationcited by 71
  31. 2022Density-aware NeRF Ensembles: Quantifying Predictive Uncertainty in Neural Radiance Fieldscited by 58
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  33. 2023NeU-NBV: Next Best View Planning Using Uncertainty Estimation in Image-Based Neural Renderingcited by 53
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  35. 2023Nerflets: Local Radiance Fields for Efficient Structure-Aware 3D Scene Representation from 2D Supervisioncited by 44
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  37. 2022RC-MVSNet: Unsupervised Multi-View Stereo with Neural Renderingcited by 30
  38. 2023NeRF-Loc: Visual Localization with Conditional Neural Radiance Fieldcited by 29

50 most cited of 54 All 54 (JSON)

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Cited by year (2026 to 7 Oct)

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

3 papers.

  1. 2026Predictive Photometric Uncertainty in Gaussian Splatting for Novel View Synthesiscited by 5
  2. 2025PRIMU: Uncertainty Estimation for Novel Views in Gaussian Splatting from Primitive-Based Representations of Error and Coveragecited by 4
  3. 2026Uncertainty-driven 3D Gaussian Splatting Active Mapping via Anisotropic Visibility Fieldcited by 4