mlsanityData to 7 Oct 2026

Zero-Shot Image Restoration Using Denoising Diffusion Null-Space Model

arXiv 2212.00490 ↗First posted 1 Dec 2022cs.CVcited by 574

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

Abstract (arXiv)

Most existing Image Restoration (IR) models are task-specific, which can not be generalized to different degradation operators. In this work, we propose the Denoising Diffusion Null-Space Model (DDNM), a novel zero-shot framework for arbitrary linear IR problems, including but not limited to image super-resolution, colorization, inpainting, compressed sensing, and deblurring. DDNM only needs a pre-trained off-the-shelf diffusion model as the generative prior, without any extra training or network modifications. By refining only the null-space contents during the reverse diffusion process, we can yield diverse results satisfying both data consistency and realness. We further propose an enhanced and robust version, dubbed DDNM+, to support noisy restoration and improve restoration quality for hard tasks. Our experiments on several IR tasks reveal that DDNM outperforms other state-of-the-art zero-shot IR methods. We also demonstrate that DDNM+ can solve complex real-world applications, e.g., old photo restoration.

Key facts. Cited by 574 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 34 of its 44 references that are in the map. First posted on arXiv 1 Dec 2022.

Builds on

34 of 44 references.

Closest ancestors · 4

Same direction, newest first

  1. 2022Diffusion Posterior Sampling for General Noisy Inverse Problems29 Sep
  2. 2022Improving Diffusion Models for Inverse Problems using Manifold Constraints2 Jun
  3. 2022Denoising Diffusion Restoration Models27 Jan
  4. 2021Deblurring via Stochastic Refinement5 Dec

Other references · 30

  1. 2020Denoising Diffusion Probabilistic Modelscited by 20,851
  2. 2020Denoising Diffusion Implicit Modelscited by 9,655
  3. 2020Score-Based Generative Modeling through Stochastic Differential Equationscited by 8,964
  4. 2021Diffusion Models Beat GANs on Image Synthesiscited by 8,185
  5. 2018A Style-Based Generator Architecture for Generative Adversarial Networkscited by 5,986
  6. 2022Generative Adversarial Networkscited by 5,603
  7. 2017Neural Discrete Representation Learningcited by 4,650
  8. 2019Generative Modeling by Estimating Gradients of the Data Distributioncited by 4,067
  9. 2013Auto-Encoding Variational Bayescited by 3,980
  10. 2019Analyzing and Improving the Image Quality of StyleGANcited by 3,580
  11. 2022Video Diffusion Modelscited by 2,280
  12. 2021SwinIR: Image Restoration Using Swin Transformercited by 1,869
18 more
  1. 2021Image Super-Resolution via Iterative Refinementcited by 1,506
  2. 2022RePaint: Inpainting using Denoising Diffusion Probabilistic Modelscited by 1,419
  3. 2021Palette: Image-to-Image Diffusion Modelscited by 1,296
  4. 2014Image Super-Resolution Using Deep Convolutional Networkscited by 1,218
  5. 2021Alias-Free Generative Adversarial Networkscited by 1,181
  6. 2021ILVR: Conditioning Method for Denoising Diffusion Probabilistic Modelscited by 634
  7. 2021Designing a Practical Degradation Model for Deep Blind Image Super-Resolutioncited by 524
  8. 2021Solving Inverse Problems in Medical Imaging with Score-Based Generative Modelscited by 514
  9. 2020PULSE: Self-Supervised Photo Upsampling via Latent Space Exploration of Generative Modelscited by 358
  10. 2021Towards Real-World Blind Face Restoration with Generative Facial Priorcited by 347
  11. 2020Deep Unfolding Network for Image Super-Resolutioncited by 253
  12. 2020Exploiting Deep Generative Prior for Versatile Image Restoration and Manipulationcited by 225
  13. 2021GAN Prior Embedded Network for Blind Face Restoration in the Wildcited by 197
  14. 2020GLEAN: Generative Latent Bank for Large-Factor Image Super-Resolutioncited by 158
  15. 2019Explorable Super Resolutioncited by 44
  16. 2019Deep Decomposition Learning for Inverse Imaging Problemscited by 25
  17. 2022GAN Prior based Null-Space Learning for Consistent Super-Resolutioncited by 22
  18. 2022Panini-Net: GAN Prior Based Degradation-Aware Feature Interpolation for Face Restorationcited by 12

Built on by

Cited by year (2026 to 7 Oct)

Citing papers per year: 2022: 1; 2023: 102; 2024: 191; 2025: 158; 2026: 122.

574 papers.

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By area:

  1. 2023Exploiting Diffusion Prior for Real-World Image Super-Resolutioncited by 486
  2. 2023Universal Guidance for Diffusion Modelscited by 426
  3. 2023SeeSR: Towards Semantics-Aware Real-World Image Super-Resolutioncited by 311
  4. 2023FreeDoM: Training-Free Energy-Guided Conditional Diffusion Modelcited by 290
  5. 2024Scaling Up to Excellence: Practicing Model Scaling for Photo-Realistic Image Restoration In the Wildcited by 281
  6. 2023DiffBIR: Towards Blind Image Restoration with Generative Diffusion Priorcited by 255
  7. 2024One-Step Effective Diffusion Network for Real-World Image Super-Resolutioncited by 243
  8. 2023I2SB: Image-to-Image Schr"odinger Bridgecited by 214
  9. 2024Diffusion Model-Based Image Editing: A Surveycited by 212
  10. 2023Solving Inverse Problems with Latent Diffusion Models via Hard Data Consistencycited by 180
  11. 2024A Survey on Diffusion Models for Inverse Problemscited by 173
  12. 2024Improving Diffusion Inverse Problem Solving with Decoupled Noise Annealingcited by 157
38 more
  1. 2023Solving Linear Inverse Problems Provably via Posterior Sampling with Latent Diffusion Modelscited by 156
  2. 2023DDFM: Denoising Diffusion Model for Multi-Modality Image Fusioncited by 153
  3. 2023Manifold Preserving Guided Diffusioncited by 153
  4. 2023Upscale-A-Video: Temporal-Consistent Diffusion Model for Real-World Video Super-Resolutioncited by 131
  5. 2023Decomposed Diffusion Sampler for Accelerating Large-Scale Inverse Problemscited by 129
  6. 2024Derivative-Free Guidance in Continuous and Discrete Diffusion Models with Soft Value-Based Decodingcited by 127
  7. 2024D-Flow: Differentiating through Flows for Controlled Generationcited by 115
  8. 2023Diffusion Models for Image Restoration and Enhancement: A Comprehensive Surveycited by 108
  9. 2024Self-Rectifying Diffusion Sampling with Perturbed-Attention Guidancecited by 108
  10. 2023HumanTOMATO: Text-aligned Whole-body Motion Generationcited by 103
  11. 2024TFG: Unified Training-Free Guidance for Diffusion Modelscited by 103
  12. 2023AutoDIR: Automatic All-in-One Image Restoration with Latent Diffusioncited by 98
  13. 2022DifFace: Blind Face Restoration with Diffused Error Contractioncited by 96
  14. 2024Principled Probabilistic Imaging using Diffusion Models as Plug-and-Play Priorscited by 93
  15. 2024PnP-Flow: Plug-and-Play Image Restoration with Flow Matchingcited by 92
  16. 2023Hierarchical Integration Diffusion Model for Realistic Image Deblurringcited by 87
  17. 2023Wavelet-based Fourier Information Interaction with Frequency Diffusion Adjustment for Underwater Image Restorationcited by 86
  18. 2024Arbitrary-steps Image Super-resolution via Diffusion Inversioncited by 85
  19. 2024TSD-SR: One-Step Diffusion with Target Score Distillation for Real-World Image Super-Resolutioncited by 83
  20. 2024NVS-Solver: Video Diffusion Model as Zero-Shot Novel View Synthesizercited by 79
  21. 2023Beyond First-Order Tweedie: Solving Inverse Problems using Latent Diffusioncited by 78
  22. 2023Robustness of AI-Image Detectors: Fundamental Limits and Practical Attackscited by 75
  23. 2024Selective Hourglass Mapping for Universal Image Restoration Based on Diffusion Modelcited by 73
  24. 2025Yume: An Interactive World Generation Modelcited by 73
  25. 2023PhysHOI: Physics-Based Imitation of Dynamic Human-Object Interactioncited by 72
  26. 2024An Overview of Diffusion Models: Applications, Guided Generation, Statistical Rates and Optimizationcited by 72
  27. 2023AutoDiffusion: Training-Free Optimization of Time Steps and Architectures for Automated Diffusion Model Accelerationcited by 70
  28. 2023Training-free Linear Image Inverses via Flowscited by 70
  29. 2024LightenDiffusion: Unsupervised Low-Light Image Enhancement with Latent-Retinex Diffusion Modelscited by 70
  30. 2024Guidance with Spherical Gaussian Constraint for Conditional Diffusioncited by 69
  31. 2023Residual Denoising Diffusion Modelscited by 68
  32. 2025InverseBench: Benchmarking Plug-and-Play Diffusion Priors for Inverse Problems in Physical Sciencescited by 67
  33. 2023CoSeR: Bridging Image and Language for Cognitive Super-Resolutioncited by 66
  34. 2023Direct Diffusion Bridge using Data Consistency for Inverse Problemscited by 65
  35. 2025FlowDPS: Flow-Driven Posterior Sampling for Inverse Problemscited by 65
  36. 2024Efficient Diffusion Model for Image Restoration by Residual Shiftingcited by 64
  37. 2024Degradation-Guided One-Step Image Super-Resolution with Diffusion Priorscited by 64
  38. 2024DreamClear: High-Capacity Real-World Image Restoration with Privacy-Safe Dataset Curationcited by 64

50 most cited of 574 All 574 (JSON)

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  1. 2023Restoration based Generative Models
  2. 2022JPEG Artifact Correction using Denoising Diffusion Restoration Models
  3. 2023Generative Diffusion Prior for Unified Image Restoration and Enhancement
  4. 2024Denoising as Adaptation: Noise-Space Domain Adaptation for Image Restoration
  5. 2022DriftRec: Adapting diffusion models to blind JPEG restoration
  6. 2025Restoring Real-World Images with an Internal Detail Enhancement Diffusion Model
  7. 2024Consistent Diffusion: Denoising Diffusion Model with Data-Consistent Training for Image Restoration
  8. 2025Exploiting the Exact Denoising Posterior Score in Training-Free Guidance of Diffusion Models