mlsanityData to 7 Oct 2026

Noisier2Noise: Learning to Denoise from Unpaired Noisy Data

arXiv 1910.11908 ↗First posted 25 Oct 2019eess.IV cs.CVcited by 125

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Abstract (arXiv)

We present a method for training a neural network to perform image denoising without access to clean training examples or access to paired noisy training examples. Our method requires only a single noisy realization of each training example and a statistical model of the noise distribution, and is applicable to a wide variety of noise models, including spatially structured noise. Our model produces results which are competitive with other learned methods which require richer training data, and outperforms traditional non-learned denoising methods. We present derivations of our method for arbitrary additive noise, an improvement specific to Gaussian additive noise, and an extension to multiplicative Bernoulli noise.

Key facts. Cited by 125 papers in the map (data through 7 Oct 2026). First posted on arXiv 25 Oct 2019.

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2021: 15; 2022: 19; 2023: 33; 2024: 25; 2025: 18; 2026: 15.

125 papers.

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  1. 2021Neighbor2Neighbor: Self-Supervised Denoising from Single Noisy Imagescited by 171
  2. 2021Noise2Score: Tweedie's Approach to Self-Supervised Image Denoising without Clean Imagescited by 110
  3. 2022AP-BSN: Self-Supervised Denoising for Real-World Images via Asymmetric PD and Blind-Spot Networkcited by 92
  4. 2021Equivariant Imaging: Learning Beyond the Range Spacecited by 83
  5. 2022Blind2Unblind: Self-Supervised Image Denoising with Visible Blind Spotscited by 83
  6. 2023Zero-Shot Noise2Noise: Efficient Image Denoising without any Datacited by 59
  7. 2022C2N: Practical Generative Noise Modeling for Real-World Denoisingcited by 56
  8. 2022CVF-SID: Cyclic multi-Variate Function for Self-Supervised Image Denoising by Disentangling Noise from Imagecited by 45
  9. 2024Consistent Diffusion Meets Tweedie: Training Exact Ambient Diffusion Models with Noisy Datacited by 44
  10. 2021Rethinking Deep Image Prior for Denoisingcited by 38
  11. 2023LG-BPN: Local and Global Blind-Patch Network for Self-Supervised Real-World Denoisingcited by 37
  12. 2021IDR: Self-Supervised Image Denoising via Iterative Data Refinementcited by 36
38 more
  1. 2023Spatially Adaptive Self-Supervised Learning for Real-World Image Denoisingcited by 33
  2. 2024Ambient Diffusion Posterior Sampling: Solving Inverse Problems with Diffusion Models Trained on Corrupted Datacited by 32
  3. 2023MM-BSN: Self-Supervised Image Denoising for Real-World with Multi-Mask based on Blind-Spot Networkcited by 30
  4. 2022A theoretical framework for self-supervised MR image reconstruction using sub-sampling via variable density Noisier2Noisecited by 29
  5. 2021Optimal Transport for Unsupervised Denoising Learningcited by 24
  6. 2022Self-Score: Self-Supervised Learning on Score-Based Models for MRI Reconstructioncited by 23
  7. 2021FBI-Denoiser: Fast Blind Image Denoiser for Poisson-Gaussian Noisecited by 22
  8. 2022A Survey of Graph-based Deep Learning for Anomaly Detection in Distributed Systemscited by 20
  9. 2021Noise Distribution Adaptive Self-Supervised Image Denoising using Tweedie Distribution and Score Matchingcited by 18
  10. 2024How much is a noisy image worth? Data Scaling Laws for Ambient Diffusioncited by 18
  11. 2022Noise2NoiseFlow: Realistic Camera Noise Modeling without Clean Imagescited by 17
  12. 2023Exploring Efficient Asymmetric Blind-Spots for Self-Supervised Denoising in Real-World Scenarioscited by 17
  13. 2023Unleashing the Power of Self-Supervised Image Denoising: A Comprehensive Reviewcited by 17
  14. 2021Adaptive Denoising via GainTuningcited by 16
  15. 2023Score Priors Guided Deep Variational Inference for Unsupervised Real-World Single Image Denoisingcited by 15
  16. 2023FastLLVE: Real-Time Low-Light Video Enhancement with Intensity-Aware Lookup Tablecited by 15
  17. 2024CLEAR: Can Language Models Really Understand Causal Graphs?cited by 14
  18. 2023Self-Supervised Image Denoising for Real-World Images with Context-aware Transformercited by 13
  19. 2023Self-supervised Image Denoising with Downsampled Invariance Loss and Conditional Blind-Spot Networkcited by 12
  20. 2025Reversing Flow for Image Restorationcited by 10
  21. 2024Zero-Shot Adaptation for Approximate Posterior Sampling of Diffusion Models in Inverse Problemscited by 9
  22. 2023Analyzing the Sample Complexity of Self-Supervised Image Reconstruction Methodscited by 8
  23. 2023SVNR: Spatially-variant Noise Removal with Denoising Diffusioncited by 8
  24. 2023Recurrent Self-Supervised Video Denoising with Denser Receptive Fieldcited by 8
  25. 2023Self-Supervised Scalable Deep Compressed Sensingcited by 8
  26. 2023A Deep Learning Method for Simultaneous Denoising and Missing Wedge Reconstruction in Cryogenic Electron Tomographycited by 7
  27. 2024Positive2Negative: Breaking the Information-Lossy Barrier in Self-Supervised Single Image Denoisingcited by 6
  28. 2025Self-Supervised Diffusion MRI Denoising via Iterative and Stable Refinementcited by 6
  29. 2025Score-based Self-supervised MRI Denoisingcited by 6
  30. 2025Rotation-Equivariant Self-Supervised Method in Image Denoisingcited by 6
  31. 2022Patch-Craft Self-Supervised Training for Correlated Image Denoisingcited by 5
  32. 2023K-band: Self-supervised MRI Reconstruction via Stochastic Gradient Descent over K-space Subsetscited by 5
  33. 2023Recurrent Spike-based Image Restoration under General Illuminationcited by 5
  34. 2024Perspective-Equivariance for Unsupervised Imaging with Camera Geometrycited by 5
  35. 2025Noisier2Inverse: Self-Supervised Learning for Image Reconstruction with Correlated Noisecited by 5
  36. 2025StableMotion: Training Motion Cleanup Models with Unpaired Corrupted Datacited by 5
  37. 2026Self-Supervised Learning from Noisy and Incomplete Datacited by 5
  38. 2022Robust Deep Ensemble Method for Real-world Image Denoisingcited by 4

50 most cited of 125 All 125 (JSON)