mlsanityData to 7 Oct 2026

Rethinking Deep Image Prior for Denoising

arXiv 2108.12841 ↗First posted 29 Aug 2021eess.IV cs.CVcited by 38

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Abstract (arXiv)

Deep image prior (DIP) serves as a good inductive bias for diverse inverse problems. Among them, denoising is known to be particularly challenging for the DIP due to noise fitting with the requirement of an early stopping. To address the issue, we first analyze the DIP by the notion of effective degrees of freedom (DF) to monitor the optimization progress and propose a principled stopping criterion before fitting to noise without access of a paired ground truth image for Gaussian noise. We also propose the `stochastic temporal ensemble (STE)' method for incorporating techniques to further improve DIP's performance for denoising. We additionally extend our method to Poisson noise. Our empirical validations show that given a single noisy image, our method denoises the image while preserving rich textual details. Further, our approach outperforms prior arts in LPIPS by large margins with comparable PSNR and SSIM on seven different datasets.

Key facts. Cited by 38 papers in the map (data through 7 Oct 2026). Builds on 20 of its 57 references that are in the map. First posted on arXiv 29 Aug 2021.

Builds on

20 of 57 references.

References · 20

  1. 2018The Unreasonable Effectiveness of Deep Features as a Perceptual Metriccited by 11,029
  2. 2016Photo-Realistic Single Image Super-Resolution Using a Generative Adversarial Networkcited by 1,898
  3. 2016Beyond a Gaussian Denoiser: Residual Learning of Deep CNN for Image Denoisingcited by 1,352
  4. 2017Deep Image Priorcited by 1,097
  5. 2019On the Variance of the Adaptive Learning Rate and Beyondcited by 763
  6. 2017The Perception-Distortion Tradeoffcited by 582
  7. 2018Noise2Noise: Learning Image Restoration without Clean Datacited by 526
  8. 2017FFDNet: Toward a Fast and Flexible Solution for CNN based Image Denoisingcited by 509
  9. 2017Learning Deep CNN Denoiser Prior for Image Restorationcited by 407
  10. 2017Benchmarking Denoising Algorithms with Real Photographscited by 209
  11. 2019High-Quality Self-Supervised Deep Image Denoisingcited by 161
  12. 2017Data Distillation: Towards Omni-Supervised Learningcited by 126
8 more
  1. 2019Noisier2Noise: Learning to Denoise from Unpaired Noisy Datacited by 125
  2. 2018Deep Decoder: Concise Image Representations from Untrained Non-convolutional Networkscited by 120
  3. 2018Neural Nearest Neighbors Networkscited by 98
  4. 2019DeepRED: Deep Image Prior Powered by REDcited by 84
  5. 2019A Bayesian Perspective on the Deep Image Priorcited by 52
  6. 2018Unsupervised Learning with Stein's Unbiased Risk Estimatorcited by 47
  7. 2018Training Deep Learning Based Denoisers without Ground Truth Datacited by 43
  8. 2016Degrees of Freedom in Deep Neural Networkscited by 14

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2021: 3; 2022: 6; 2023: 11; 2024: 12; 2025: 3; 2026: 3.

38 papers.

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  1. 2021Early Stopping for Deep Image Priorcited by 44
  2. 2023GSURE-Based Diffusion Model Training with Corrupted Datacited by 40
  3. 2024Deep Diffusion Image Prior for Efficient OOD Adaptation in 3D Inverse Problemscited by 21
  4. 2022Learning to Immunize Images for Tamper Localization and Self-Recoverycited by 19
  5. 2023NCP: Neural Correspondence Prior for Effective Unsupervised Shape Matchingcited by 18
  6. 2021An Educated Warm Start For Deep Image Prior-Based Micro CT Reconstructioncited by 16
  7. 2021Self-Validation: Early Stopping for Single-Instance Deep Generative Priorscited by 15
  8. 2022Equivariance and Invariance Inductive Bias for Learning from Insufficient Datacited by 14
  9. 2023The Devil is in the Upsampling: Architectural Decisions Made Simpler for Denoising with Deep Image Priorcited by 11
  10. 2024Analysis of Deep Image Prior and Exploiting Self-Guidance for Image Reconstructioncited by 11
  11. 2023Deep Internal Learning: Deep Learning from a Single Inputcited by 9
  12. 2023Revisiting Implicit Neural Representations in Low-Level Visioncited by 8
26 more
  1. 2024Patch-Based Diffusion Models Beat Whole-Image Models for Mismatched Distribution Inverse Problemscited by 8
  2. 2025A Baseline Method for Removing Invisible Image Watermarks using Deep Image Priorcited by 6
  3. 2023Recurrent Spike-based Image Restoration under General Illuminationcited by 5
  4. 2024Sensitivity Decouple Learning for Image Compression Artifacts Reductioncited by 5
  5. 2022Linear Combinations of Patches are Unreasonably Effective for Single-Image Denoisingcited by 4
  6. 2024Image Denoising Using Green Channel Priorcited by 4
  7. 2025YOND: Practical Blind Raw Image Denoising Free from Camera-Specific Data Dependencycited by 4
  8. 2022Priors in Deep Image Restoration and Enhancement: A Surveycited by 3
  9. 2024Masked Pre-training Enables Universal Zero-shot Denoisercited by 3
  10. 2022CFNet: Conditional Filter Learning with Dynamic Noise Estimation for Real Image Denoisingcited by 2
  11. 2023SVD-DIP: Overcoming the Overfitting Problem in DIP-based CT Reconstructioncited by 2
  12. 2023Learning Self-Prior for Mesh Inpainting Using Self-Supervised Graph Convolutional Networkscited by 2
  13. 2024Optimal Eye Surgeon: Finding Image Priors through Sparse Generators at Initializationcited by 2
  14. 2022Residual Back Projection With Untrained Neural Networkscited by 1
  15. 2023Image Reconstruction via Deep Image Prior Subspacescited by 1
  16. 2024On normalization-equivariance properties of supervised and unsupervised denoising methods: a surveycited by 1
  17. 2024SDIP: Self-Reinforcement Deep Image Prior Framework for Image Processingcited by 1
  18. 2024Optimize the Unseen -- Fast NeRF Cleanup with Free Space Priorcited by 1
  19. 2025Deep Spectral Priorcited by 1
  20. 2023Generalizable Denoising of Microscopy Images using Generative Adversarial Networks and Contrastive Learningcited by 0
  21. 2023JPEG Information Regularized Deep Image Prior for Denoisingcited by 0
  22. 2024A unified framework of non-local parametric methods for image denoisingcited by 0
  23. 2024Chasing Better Deep Image Priors between Over- and Under-parameterizationcited by 0
  24. 2026Automating Parameter Selection in Deep Image Prior for Fluorescence Microscopy Image Denoising via Similarity-Based Parameter Transfercited by 0
  25. 2026Compressive sensing inspired self-supervised single-pixel imagingcited by 0
  26. 2026Dual-Integrated Low-Latency Single-Lens Infrared Computational Imaging for Object Detectioncited by 0