mlsanityData to 7 Oct 2026

Taming Diffusion Models for Image Restoration: A Review

arXiv 2409.10353 ↗First posted 16 Sep 2024cs.CVcited by 12

On the map: Diffusion models → Inverse problems and image restoration

Abstract (arXiv)

Diffusion models have achieved remarkable progress in generative modelling, particularly in enhancing image quality to conform to human preferences. Recently, these models have also been applied to low-level computer vision for photo-realistic image restoration (IR) in tasks such as image denoising, deblurring, dehazing, etc. In this review paper, we introduce key constructions in diffusion models and survey contemporary techniques that make use of diffusion models in solving general IR tasks. Furthermore, we point out the main challenges and limitations of existing diffusion-based IR frameworks and provide potential directions for future work.

Key facts. Cited by 12 papers in the map (data through 7 Oct 2026). Placed in Inverse problems and image restoration, one of 14 directions in Diffusion models. Builds on 65 of its 92 references that are in the map. First posted on arXiv 16 Sep 2024.

Builds on

65 of 92 references.

Closest ancestors · 17

Same direction, newest first

  1. 2024Posterior Sampling with Denoising Oracles via Tilted Transport30 Jun
  2. 2024Equipping Diffusion Models with Differentiable Spatial Entropy for Low-Light Image Enhancement15 Apr
  3. 2024Photo-Realistic Image Restoration in the Wild with Controlled Vision-Language Models15 Apr
  4. 2024Divide-and-Conquer Posterior Sampling for Denoising Diffusion Priors18 Mar
  5. 2023Image Restoration Through Generalized Ornstein-Uhlenbeck Bridge16 Dec
  6. 2023SeeSR: Towards Semantics-Aware Real-World Image Super-Resolution27 Nov
  7. 2023DiffBIR: Towards Blind Image Restoration with Generative Diffusion Prior29 Aug
  8. 2023Low-Light Image Enhancement with Wavelet-based Diffusion Models1 Jun
  9. 2023Exploiting Diffusion Prior for Real-World Image Super-Resolution11 May
  10. 2023Refusion: Enabling Large-Size Realistic Image Restoration with Latent-Space Diffusion Models17 Apr
  11. 2022Zero-Shot Image Restoration Using Denoising Diffusion Null-Space Model1 Dec
  12. 2022Diffusion Posterior Sampling for General Noisy Inverse Problems29 Sep
5 more
  1. 2022Restoring Vision in Adverse Weather Conditions with Patch-Based Denoising Diffusion Models29 Jul
  2. 2022Improving Diffusion Models for Inverse Problems using Manifold Constraints2 Jun
  3. 2022Denoising Diffusion Restoration Models27 Jan
  4. 2021Come-Closer-Diffuse-Faster: Accelerating Conditional Diffusion Models for Inverse Problems through Stochastic Contraction9 Dec
  5. 2021Deblurring via Stochastic Refinement5 Dec

Other references · 48

  1. 2017Attention Is All You Needcited by 59,932
  2. 2020Denoising Diffusion Probabilistic Modelscited by 20,851
  3. 2021High-Resolution Image Synthesis with Latent Diffusion Modelscited by 18,694
  4. 2020Denoising Diffusion Implicit Modelscited by 9,655
  5. 2020Score-Based Generative Modeling through Stochastic Differential Equationscited by 8,964
  6. 2021Diffusion Models Beat GANs on Image Synthesiscited by 8,185
  7. 2015Deep Unsupervised Learning using Nonequilibrium Thermodynamicscited by 7,005
  8. 2022Photorealistic Text-to-Image Diffusion Models with Deep Language Understandingcited by 6,322
  9. 2022Generative Adversarial Networkscited by 5,603
  10. 2023Adding Conditional Control to Text-to-Image Diffusion Modelscited by 5,466
  11. 2022Flow Matching for Generative Modelingcited by 5,426
  12. 2019Generative Modeling by Estimating Gradients of the Data Distributioncited by 4,067
36 more
  1. 2016Perceptual Losses for Real-Time Style Transfer and Super-Resolutioncited by 2,678
  2. 2022DPM-Solver: A Fast ODE Solver for Diffusion Probabilistic Model Sampling in Around 10 Stepscited by 1,961
  3. 2016Photo-Realistic Single Image Super-Resolution Using a Generative Adversarial Networkcited by 1,898
  4. 2022Imagen Video: High Definition Video Generation with Diffusion Modelscited by 1,765
  5. 2021Image Super-Resolution via Iterative Refinementcited by 1,506
  6. 2016Context Encoders: Feature Learning by Inpaintingcited by 1,424
  7. 2016Beyond a Gaussian Denoiser: Residual Learning of Deep CNN for Image Denoisingcited by 1,352
  8. 2021Palette: Image-to-Image Diffusion Modelscited by 1,296
  9. 2018ESRGAN: Enhanced Super-Resolution Generative Adversarial Networkscited by 1,250
  10. 2022Diffusion Models: A Comprehensive Survey of Methods and Applicationscited by 1,107
  11. 2022Diffusion Models in Vision: A Surveycited by 1,008
  12. 2021Real-ESRGAN: Training Real-World Blind Super-Resolution with Pure Synthetic Datacited by 961
  13. 2018Computational Optimal Transportcited by 765
  14. 2021ILVR: Conditioning Method for Denoising Diffusion Probabilistic Modelscited by 634
  15. 2021Diffusion Schr"odinger Bridge with Applications to Score-Based Generative Modelingcited by 594
  16. 2017Benchmarking Single Image Dehazing and Beyondcited by 445
  17. 2019DeblurGAN-v2: Deblurring (Orders-of-Magnitude) Faster and Bettercited by 361
  18. 2024Scaling Up to Excellence: Practicing Model Scaling for Photo-Realistic Image Restoration In the Wildcited by 281
  19. 2021How to Train Your Energy-Based Modelscited by 271
  20. 2021TransWeather: Transformer-based Restoration of Images Degraded by Adverse Weather Conditionscited by 243
  21. 2022BBDM: Image-to-image Translation with Brownian Bridge Diffusion Modelscited by 222
  22. 2023Practical and Asymptotically Exact Conditional Sampling in Diffusion Modelscited by 218
  23. 2021Likelihood Training of Schr"odinger Bridge using Forward-Backward SDEs Theorycited by 216
  24. 2023I2SB: Image-to-Image Schr"odinger Bridgecited by 214
  25. 2022Dual Diffusion Implicit Bridges for Image-to-Image Translationcited by 212
  26. 2023Image Restoration with Mean-Reverting Stochastic Differential Equationscited by 182
  27. 2023Denoising Diffusion Bridge Modelscited by 171
  28. 2019RankSRGAN: Generative Adversarial Networks with Ranker for Image Super-Resolutioncited by 145
  29. 2022ShadowDiffusion: When Degradation Prior Meets Diffusion Model for Shadow Removalcited by 102
  30. 2019Shadow Removal via Shadow Image Decompositioncited by 96
  31. 2020NBNet: Noise Basis Learning for Image Denoising with Subspace Projectioncited by 77
  32. 2023Towards Coherent Image Inpainting Using Denoising Diffusion Implicit Modelscited by 61
  33. 2018Physics-Based Generative Adversarial Models for Image Restoration and Beyondcited by 37
  34. 2020How to Train Your Energy-Based Model for Regressioncited by 23
  35. 2023Deep Optimal Transport: A Practical Algorithm for Photo-realistic Image Restorationcited by 15
  36. 2024Conditioning diffusion models by explicit forward-backward bridgingcited by 11

Built on by

Cited by year (2026 to 7 Oct)

Citing papers per year: 2024: 1; 2025: 8; 2026: 3.

12 papers.

  1. 2024Free Hunch: Denoiser Covariance Estimation for Diffusion Models Without Extra Costscited by 14
  2. 2025OMGSR: You Only Need One Mid-timestep Guidance for Real-World Image Super-Resolutioncited by 14
  3. 2025Residual Diffusion Bridge Model for Image Restorationcited by 14
  4. 2025SIR-DIFF: Sparse Image Sets Restoration with Multi-View Diffusion Modelcited by 5
  5. 2025DGSolver: Diffusion Generalist Solver with Universal Posterior Sampling for Image Restorationcited by 5
  6. 2025Generative diffusion posterior sampling for informative likelihoodscited by 4
  7. 2025Diffusion differentiable resamplingcited by 2
  8. 2026A Stability Benchmark of Generative Regularizers for Inverse Problemscited by 1
  9. 2026SeqLoRA: Bilevel Orthogonal Adaptation for Continual Multi-Concept Generationcited by 1
  10. 2025StableMotion: One-Step Motion Estimation with Diffusion Priorcited by 0
  11. 2025AODDiff: Probabilistic Reconstruction of Aerosol Optical Depth via Diffusion-based Bayesian Inferencecited by 0
  12. 2026Nonparametric Deconvolution and Denoising using Simulation Based Inferencecited by 0

Similar, not cited

Close in wording, no citation either way

  1. 2023Diffusion Models for Image Restoration and Enhancement: A Comprehensive Survey
  2. 2024Diffusion Models in Low-Level Vision: A Survey
  3. 2023Restoration based Generative Models
  4. 2025Elucidating and Endowing the Diffusion Training Paradigm for General Image Restoration
  5. 2023A Unified Conditional Framework for Diffusion-based Image Restoration
  6. 2023Real-World Denoising via Diffusion Model
  7. 2024Efficient Diffusion Model for Image Restoration by Residual Shifting
  8. 2024A Survey on Diffusion Models for Inverse Problems