# NAN: Noise-Aware NeRFs for Burst-Denoising

arXiv: https://arxiv.org/abs/2204.04668 · HTML: https://mlsanity.com/paper/2204.04668/

## Key facts

- Cited by 48 papers in the map (data through 14 Oct 2026).
- Builds on 27 of its 34 references that are in the map.
- First posted on arXiv 10 Apr 2022.

## Builds on (most cited first, 27 of 27)

- [Attention Is All You Need](https://mlsanity.com/paper/1706.03762/) (2017)
- [The Unreasonable Effectiveness of Deep Features as a Perceptual Metric](https://mlsanity.com/paper/1801.03924/) (2018)
- [Instant Neural Graphics Primitives with a Multiresolution Hash Encoding](https://mlsanity.com/paper/2201.05989/) (2022)
- [pixelNeRF: Neural Radiance Fields from One or Few Images](https://mlsanity.com/paper/2012.02190/) (2020)
- [D-NeRF: Neural Radiance Fields for Dynamic Scenes](https://mlsanity.com/paper/2011.13961/) (2020)
- [NeRF in the Wild: Neural Radiance Fields for Unconstrained Photo Collections](https://mlsanity.com/paper/2008.02268/) (2020)
- [Nerfies: Deformable Neural Radiance Fields](https://mlsanity.com/paper/2011.12948/) (2020)
- [PWC-Net: CNNs for Optical Flow Using Pyramid, Warping, and Cost Volume](https://mlsanity.com/paper/1709.02371/) (2017)
- [PlenOctrees for Real-time Rendering of Neural Radiance Fields](https://mlsanity.com/paper/2103.14024/) (2021)
- [IBRNet: Learning Multi-View Image-Based Rendering](https://mlsanity.com/paper/2102.13090/) (2021)
- [KiloNeRF: Speeding up Neural Radiance Fields with Thousands of Tiny MLPs](https://mlsanity.com/paper/2103.13744/) (2021)
- [Local Light Field Fusion: Practical View Synthesis with Prescriptive Sampling Guidelines](https://mlsanity.com/paper/1905.00889/) (2019)
- [BARF: Bundle-Adjusting Neural Radiance Fields](https://mlsanity.com/paper/2104.06405/) (2021)
- [FastNeRF: High-Fidelity Neural Rendering at 200FPS](https://mlsanity.com/paper/2103.10380/) (2021)
- [Baking Neural Radiance Fields for Real-Time View Synthesis](https://mlsanity.com/paper/2103.14645/) (2021)
- [Advances in Neural Rendering](https://mlsanity.com/paper/2111.05849/) (2021)
- [NeRF in the Dark: High Dynamic Range View Synthesis from Noisy Raw Images](https://mlsanity.com/paper/2111.13679/) (2021)
- [State of the Art on Neural Rendering](https://mlsanity.com/paper/2004.03805/) (2020)
- [Neural Radiance Flow for 4D View Synthesis and Video Processing](https://mlsanity.com/paper/2012.09790/) (2020)
- [Self-Calibrating Neural Radiance Fields](https://mlsanity.com/paper/2108.13826/) (2021)
- [Burst Denoising with Kernel Prediction Networks](https://mlsanity.com/paper/1712.02327/) (2017)
- [EpicFlow: Edge-Preserving Interpolation of Correspondences for Optical Flow](https://mlsanity.com/paper/1501.02565/) (2015)
- [Handheld Mobile Photography in Very Low Light](https://mlsanity.com/paper/1910.11336/) (2019)
- [Deep Burst Denoising](https://mlsanity.com/paper/1712.05790/) (2017)
- [Basis Prediction Networks for Effective Burst Denoising with Large Kernels](https://mlsanity.com/paper/1912.04421/) (2019)
- [Deep Reparametrization of Multi-Frame Super-Resolution and Denoising](https://mlsanity.com/paper/2108.08286/) (2021)
- [Iterative Residual CNNs for Burst Photography Applications](https://mlsanity.com/paper/1811.12197/) (2018)

## Built on by (most cited first, 30 of 48)

- [NeRF: Neural Radiance Field in 3D Vision: A Comprehensive Review (Updated Post-Gaussian Splatting)](https://mlsanity.com/paper/2210.00379/) (2022)
- [SeaThru-NeRF: Neural Radiance Fields in Scattering Media](https://mlsanity.com/paper/2304.07743/) (2023)
- [SimpleNeRF: Regularizing Sparse Input Neural Radiance Fields with Simpler Solutions](https://mlsanity.com/paper/2309.03955/) (2023)
- [ExBluRF: Efficient Radiance Fields for Extreme Motion Blurred Images](https://mlsanity.com/paper/2309.08957/) (2023)
- [Aleth-NeRF: Illumination Adaptive NeRF with Concealing Field Assumption](https://mlsanity.com/paper/2312.09093/) (2023)
- [HDR-GS: Efficient High Dynamic Range Novel View Synthesis at 1000x Speed via Gaussian Splatting](https://mlsanity.com/paper/2405.15125/) (2024)
- [DDN-SLAM: Real-time Dense Dynamic Neural Implicit SLAM](https://mlsanity.com/paper/2401.01545/) (2024)
- [DyBluRF: Dynamic Neural Radiance Fields from Blurry Monocular Video](https://mlsanity.com/paper/2403.10103/) (2024)
- [NTIRE 2025 Challenge on Efficient Burst HDR and Restoration: Datasets, Methods, and Results](https://mlsanity.com/paper/2505.12089/) (2025)
- [Benchmarking Robustness in Neural Radiance Fields](https://mlsanity.com/paper/2301.04075/) (2023)
- [Leveraging Thermal Modality to Enhance Reconstruction in Low-Light Conditions](https://mlsanity.com/paper/2403.14053/) (2024)
- [Hyperspectral Neural Radiance Fields](https://mlsanity.com/paper/2403.14839/) (2024)
- [USB-NeRF: Unrolling Shutter Bundle Adjusted Neural Radiance Fields](https://mlsanity.com/paper/2310.02687/) (2023)
- [DehazeNeRF: Multiple Image Haze Removal and 3D Shape Reconstruction using Neural Radiance Fields](https://mlsanity.com/paper/2303.11364/) (2023)
- [Aleth-NeRF: Low-light Condition View Synthesis with Concealing Fields](https://mlsanity.com/paper/2303.05807/) (2023)
- [Shakes on a Plane: Unsupervised Depth Estimation from Unstabilized Photography](https://mlsanity.com/paper/2212.12324/) (2022)
- [SVNR: Spatially-variant Noise Removal with Denoising Diffusion](https://mlsanity.com/paper/2306.16052/) (2023)
- [RainyScape: Unsupervised Rainy Scene Reconstruction using Decoupled Neural Rendering](https://mlsanity.com/paper/2404.11401/) (2024)
- [Unifying Color and Lightness Correction with View-Adaptive Curve Adjustment for Robust 3D Novel View Synthesis](https://mlsanity.com/paper/2602.18322/) (2026)
- [Colorizing Monochromatic Radiance Fields](https://mlsanity.com/paper/2402.12184/) (2024)
- [CoMoGaussian: Continuous Motion-Aware Gaussian Splatting from Motion-Blurred Images](https://mlsanity.com/paper/2503.05332/) (2025)
- [Plenodium: UnderWater 3D Scene Reconstruction with Plenoptic Medium Representation](https://mlsanity.com/paper/2505.21258/) (2025)
- [Neural Volume Super-Resolution](https://mlsanity.com/paper/2212.04666/) (2022)
- [Efficient View Synthesis and 3D-based Multi-Frame Denoising with Multiplane Feature Representations](https://mlsanity.com/paper/2303.18139/) (2023)
- [SonarSplat: Novel View Synthesis of Imaging Sonar via Gaussian Splatting](https://mlsanity.com/paper/2504.00159/) (2025)
- [MF-NeRF: Memory Efficient NeRF with Mixed-Feature Hash Table](https://mlsanity.com/paper/2304.12587/) (2023)
- [RaFE: Generative Radiance Fields Restoration](https://mlsanity.com/paper/2404.03654/) (2024)
- [NIR-Assisted Image Denoising: A Selective Fusion Approach and A Real-World Benchmark Dataset](https://mlsanity.com/paper/2404.08514/) (2024)
- [Sparse-DeRF: Deblurred Neural Radiance Fields from Sparse View](https://mlsanity.com/paper/2407.06613/) (2024)
- [WaterHE-NeRF: Water-ray Tracing Neural Radiance Fields for Underwater Scene Reconstruction](https://mlsanity.com/paper/2312.06946/) (2023)

## Abstract (arXiv)

Burst denoising is now more relevant than ever, as computational photography helps overcome sensitivity issues inherent in mobile phones and small cameras. A major challenge in burst-denoising is in coping with pixel misalignment, which was so far handled with rather simplistic assumptions of simple motion, or the ability to align in pre-processing. Such assumptions are not realistic in the presence of large motion and high levels of noise. We show that Neural Radiance Fields (NeRFs), originally suggested for physics-based novel-view rendering, can serve as a powerful framework for burst denoising. NeRFs have an inherent capability of handling noise as they integrate information from multiple images, but they are limited in doing so, mainly since they build on pixel-wise operations which are suitable to ideal imaging conditions. Our approach, termed NAN, leverages inter-view and spatial information in NeRFs to better deal with noise. It achieves state-of-the-art results in burst denoising and is especially successful in coping with large movement and occlusions, under very high levels of noise. With the rapid advances in accelerating NeRFs, it could provide a powerful platform for denoising in challenging environments.