RobustNeRF: Ignoring Distractors with Robust Losses
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Abstract (arXiv)
Neural radiance fields (NeRF) excel at synthesizing new views given multi-view, calibrated images of a static scene. When scenes include distractors, which are not persistent during image capture (moving objects, lighting variations, shadows), artifacts appear as view-dependent effects or 'floaters'. To cope with distractors, we advocate a form of robust estimation for NeRF training, modeling distractors in training data as outliers of an optimization problem. Our method successfully removes outliers from a scene and improves upon our baselines, on synthetic and real-world scenes. Our technique is simple to incorporate in modern NeRF frameworks, with few hyper-parameters. It does not assume a priori knowledge of the types of distractors, and is instead focused on the optimization problem rather than pre-processing or modeling transient objects. More results on our page https://robustnerf.github.io.
Key facts. Cited by 101 papers in the map (data through 7 Oct 2026). Builds on 49 of its 60 references that are in the map. First posted on arXiv 2 Feb 2023.
Builds on
49 of 60 references.
References · 49
- 2018The Unreasonable Effectiveness of Deep Features as a Perceptual Metriccited by 11,029
- 2022Instant Neural Graphics Primitives with a Multiresolution Hash Encodingcited by 3,698
- 2022DreamFusion: Text-to-3D using 2D Diffusioncited by 3,006
- 2021Mip-NeRF 360: Unbounded Anti-Aliased Neural Radiance Fieldscited by 2,013
- 2021Mip-NeRF: A Multiscale Representation for Anti-Aliasing Neural Radiance Fieldscited by 1,957
- 2021NeuS: Learning Neural Implicit Surfaces by Volume Rendering for Multi-view Reconstructioncited by 1,701
- 2020pixelNeRF: Neural Radiance Fields from One or Few Imagescited by 1,574
- 2020D-NeRF: Neural Radiance Fields for Dynamic Scenescited by 1,459
- 2020NeRF in the Wild: Neural Radiance Fields for Unconstrained Photo Collectionscited by 1,230
- 2019Scene Representation Networks: Continuous 3D-Structure-Aware Neural Scene Representationscited by 864
- 2020NeRF++: Analyzing and Improving Neural Radiance Fieldscited by 857
- 2020Neural Scene Flow Fields for Space-Time View Synthesis of Dynamic Scenescited by 750
37 more
- 2022Block-NeRF: Scalable Large Scene Neural View Synthesiscited by 720
- 2021Common Objects in 3D: Large-Scale Learning and Evaluation of Real-life 3D Category Reconstructioncited by 646
- 2021UNISURF: Unifying Neural Implicit Surfaces and Radiance Fields for Multi-View Reconstructioncited by 643
- 2021BARF: Bundle-Adjusting Neural Radiance Fieldscited by 641
- 2021RegNeRF: Regularizing Neural Radiance Fields for View Synthesis from Sparse Inputscited by 614
- 2021NICE-SLAM: Neural Implicit Scalable Encoding for SLAMcited by 586
- 2021Ref-NeRF: Structured View-Dependent Appearance for Neural Radiance Fieldscited by 569
- 2020Non-Rigid Neural Radiance Fields: Reconstruction and Novel View Synthesis of a Dynamic Scene From Monocular Videocited by 470
- 2022MonoSDF: Exploring Monocular Geometric Cues for Neural Implicit Surface Reconstructioncited by 467
- 2021Baking Neural Radiance Fields for Real-Time View Synthesiscited by 465
- 2021Dynamic View Synthesis from Dynamic Monocular Videocited by 420
- 2020Space-time Neural Irradiance Fields for Free-Viewpoint Videocited by 414
- 2022Kubric: A scalable dataset generatorcited by 373
- 2021Advances in Neural Renderingcited by 365
- 2022Fast Dynamic Radiance Fields with Time-Aware Neural Voxelscited by 344
- 2021NeRF in the Dark: High Dynamic Range View Synthesis from Noisy Raw Imagescited by 336
- 2022MobileNeRF: Exploiting the Polygon Rasterization Pipeline for Efficient Neural Field Rendering on Mobile Architecturescited by 308
- 2020Neural Radiance Flow for 4D View Synthesis and Video Processingcited by 270
- 2021Urban Radiance Fieldscited by 263
- 2017A General and Adaptive Robust Loss Functioncited by 236
- 2021HyperNeRF: A Higher-Dimensional Representation for Topologically Varying Neural Radiance Fieldscited by 210
- 2021Self-Calibrating Neural Radiance Fieldscited by 204
- 2022NeRF-SLAM: Real-Time Dense Monocular SLAM with Neural Radiance Fieldscited by 188
- 2021Deblur-NeRF: Neural Radiance Fields from Blurry Imagescited by 179
- 2019Neural Volumes: Learning Dynamic Renderable Volumes from Imagescited by 173
- 2021Vision-Only Robot Navigation in a Neural Radiance Worldcited by 153
- 2022D2NeRF: Self-Supervised Decoupling of Dynamic and Static Objects from a Monocular Videocited by 136
- 2022NeuRIS: Neural Reconstruction of Indoor Scenes Using Normal Priorscited by 125
- 2021NeSF: Neural Semantic Fields for Generalizable Semantic Segmentation of 3D Scenescited by 119
- 2022DeVRF: Fast Deformable Voxel Radiance Fields for Dynamic Scenescited by 103
- 2022RelPose: Predicting Probabilistic Relative Rotation for Single Objects in the Wildcited by 102
- 2022SAMURAI: Shape And Material from Unconstrained Real-world Arbitrary Image collectionscited by 89
- 2022ReLU Fields: The Little Non-linearity That Couldcited by 87
- 2021Neural Trajectory Fields for Dynamic Novel View Synthesiscited by 85
- 2021LOLNeRF: Learn from One Lookcited by 84
- 2021NeuralDiff: Segmenting 3D objects that move in egocentric videoscited by 56
- 2022Volume Rendering Digest (for NeRF)cited by 31
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Citing papers per year: 2023: 13; 2024: 33; 2025: 27; 2026: 28.
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- 2025Difix3D+: Improving 3D Reconstructions with Single-Step Diffusion Modelscited by 160
- 2026World Reconstruction From Inconsistent Viewscited by 8
- 2025WorldWarp: Propagating 3D Geometry with Asynchronous Video Diffusioncited by 6
- 2025GaussVideoDreamer: 3D Scene Generation with Video Diffusion and Inconsistency-Aware Gaussian Splattingcited by 5
- 2026World Reconstruction From Inconsistent Views17 Mar 2026
- 2025WorldWarp: Propagating 3D Geometry with Asynchronous Video Diffusion22 Dec 2025
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- 2025Difix3D+: Improving 3D Reconstructions with Single-Step Diffusion Models3 Mar 2025
- 2023DrivingGaussian: Composite Gaussian Splatting for Surrounding Dynamic Autonomous Driving Scenescited by 359
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- 2023Bayes' Rays: Uncertainty Quantification for Neural Radiance Fieldscited by 90
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- 2023Nerfbusters: Removing Ghostly Artifacts from Casually Captured NeRFscited by 76
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- 2024Bilateral Guided Radiance Field Processingcited by 28
- 2024Splatfacto-W: A Nerfstudio Implementation of Gaussian Splatting for Unconstrained Photo Collectionscited by 28
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- 2026RoSe-SLAM: Robust Semantic-Aware Gaussian Splatting SLAM from Dynamic Monocular Videos29 Aug 2026
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- 2026Per-View Gaussian Predictions Enable Training-Free Distractor Filtering in Feed-Forward 3DGS27 Aug 2026
- 2026Coarse-to-fine Framework for Generative MEF via Implicit Neural Representation20 Jul 2026
- 2026SSA-3DGS: Unsupervised Removal of Screen-Space Artifacts for 3D Gaussian Splatting6 Jul 2026
- 2026Fast 3D Foundation Model Initialized Gaussian Splatting3 Jul 2026
- 2026MVFusion-GS: Motion-Variance Guided Temporal Attention for High-Quality Dynamic Gaussian Splatting2 Jul 2026
- 2026Rectifying Mask via Entropy for Distractor-Free 3DGS in Ambiguous Scenarios28 Jun 2026
- 2026PersistGS: Differentiable Physics for Object Permanence in 4D Gaussian Splatting2 Jun 2026
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