mlsanityData to 7 Oct 2026

Diffusion Posterior Proximal Sampling for Image Restoration

arXiv 2402.16907 ↗First posted 25 Feb 2024eess.IV cs.CV cs.LGcited by 14

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

Abstract (arXiv)

Diffusion models have demonstrated remarkable efficacy in generating high-quality samples. Existing diffusion-based image restoration algorithms exploit pre-trained diffusion models to leverage data priors, yet they still preserve elements inherited from the unconditional generation paradigm. These strategies initiate the denoising process with pure white noise and incorporate random noise at each generative step, leading to over-smoothed results. In this paper, we present a refined paradigm for diffusion-based image restoration. Specifically, we opt for a sample consistent with the measurement identity at each generative step, exploiting the sampling selection as an avenue for output stability and enhancement. The number of candidate samples used for selection is adaptively determined based on the signal-to-noise ratio of the timestep. Additionally, we start the restoration process with an initialization combined with the measurement signal, providing supplementary information to better align the generative process. Extensive experimental results and analyses validate that our proposed method significantly enhances image restoration performance while consuming negligible additional computational resources.

Key facts. Cited by 14 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 38 of its 58 references that are in the map. First posted on arXiv 25 Feb 2024.

Builds on

38 of 58 references.

Closest ancestors · 9

Same direction, newest first

  1. 2023Deep Equilibrium Diffusion Restoration with Parallel Sampling20 Nov
  2. 2023Global Structure-Aware Diffusion Process for Low-Light Image Enhancement26 Oct
  3. 2023Prompt-tuning latent diffusion models for inverse problems2 Oct
  4. 2023Solving Inverse Problems with Latent Diffusion Models via Hard Data Consistency16 Jul
  5. 2023Solving Linear Inverse Problems Provably via Posterior Sampling with Latent Diffusion Models2 Jul
  6. 2023Low-Light Image Enhancement with Wavelet-based Diffusion Models1 Jun
  7. 2023Denoising Diffusion Models for Plug-and-Play Image Restoration15 May
  8. 2022Zero-Shot Image Restoration Using Denoising Diffusion Null-Space Model1 Dec
  9. 2022Diffusion Posterior Sampling for General Noisy Inverse Problems29 Sep

Other references · 29

  1. 2020Denoising Diffusion Probabilistic Modelscited by 20,851
  2. 2021High-Resolution Image Synthesis with Latent Diffusion Modelscited by 18,694
  3. 2018The Unreasonable Effectiveness of Deep Features as a Perceptual Metriccited by 11,029
  4. 2020Score-Based Generative Modeling through Stochastic Differential Equationscited by 8,964
  5. 2014ImageNet Large Scale Visual Recognition Challengecited by 8,441
  6. 2021Diffusion Models Beat GANs on Image Synthesiscited by 8,185
  7. 2015Deep Unsupervised Learning using Nonequilibrium Thermodynamicscited by 7,005
  8. 2018A Style-Based Generator Architecture for Generative Adversarial Networkscited by 5,986
  9. 2022Elucidating the Design Space of Diffusion-Based Generative Modelscited by 2,994
  10. 2016Beyond a Gaussian Denoiser: Residual Learning of Deep CNN for Image Denoisingcited by 1,352
  11. 2021Palette: Image-to-Image Diffusion Modelscited by 1,296
  12. 2022Diffusion-LM Improves Controllable Text Generationcited by 1,006
17 more
  1. 2021Score-based Generative Modeling in Latent Spacecited by 634
  2. 2017The Perception-Distortion Tradeoffcited by 582
  3. 2021Tackling the Generative Learning Trilemma with Denoising Diffusion GANscited by 515
  4. 2021Solving Inverse Problems in Medical Imaging with Score-Based Generative Modelscited by 514
  5. 2021Score-based diffusion models for accelerated MRIcited by 308
  6. 2023Understanding Diffusion Objectives as the ELBO with Simple Data Augmentationcited by 293
  7. 2016Plug-and-Play ADMM for Image Restoration: Fixed Point Convergence and Applicationscited by 244
  8. 2023Input Perturbation Reduces Exposure Bias in Diffusion Modelscited by 88
  9. 2021Equivariant Imaging: Learning Beyond the Range Spacecited by 83
  10. 2023Alleviating Exposure Bias in Diffusion Models through Sampling with Shifted Time Stepscited by 71
  11. 2020Diverse Image Generation via Self-Conditioned GANscited by 54
  12. 2022DeS3: Adaptive Attention-driven Self and Soft Shadow Removal using ViT Similaritycited by 37
  13. 2023Exploiting the Signal-Leak Bias in Diffusion Modelscited by 36
  14. 2022Imaging with Equivariant Deep Learningcited by 35
  15. 2020TFPnP: Tuning-free Plug-and-Play Proximal Algorithm with Applications to Inverse Imaging Problemscited by 20
  16. 2022On Conditioning the Input Noise for Controlled Image Generation with Diffusion Modelscited by 14
  17. 2023Building Lane-Level Maps from Aerial Imagescited by 12

Built on by

Cited by year (2026 to 7 Oct)

Citing papers per year: 2024: 1; 2025: 11; 2026: 2.

14 papers.

Sort:

By area:

  1. 2025Diffusion models for inverse problemscited by 15
  2. 2024Constrained Diffusion with Trust Samplingcited by 9
  3. 2025Multimodal Atmospheric Super-Resolution With Deep Generative Modelscited by 8
  4. 2025Forecasting When to Forecast: Accelerating Diffusion Models with Confidence-Gated Taylorcited by 6
  5. 2025Enhancing Diffusion Model Stability for Image Restoration via Gradient Managementcited by 5
  6. 2025Deterministic Image-to-Image Translation via Denoising Brownian Bridge Models with Dual Approximatorscited by 5
  7. 2025Target-Guided Bayesian Flow Networks for Quantitatively Constrained CAD Generationcited by 2
  8. 2025Any Image Restoration via Efficient Spatial-Frequency Degradation Adaptationcited by 1
  9. 2025LatentINDIGO: An INN-Guided Latent Diffusion Algorithm for Image Restorationcited by 0
  10. 2025Dual Prompt Learning for Adapting Vision-Language Models to Downstream Image-Text Retrievalcited by 0
  11. 2025A Gradient Flow Approach to Solving Inverse Problems with Latent Diffusion Modelscited by 0
  12. 2025Uncertainty Quantification in HSI Reconstruction using Physics-Aware Diffusion Priors and Optics-Encoded Measurementscited by 0
2 more
  1. 2026MPFlow: Multi-modal Posterior-Guided Flow Matching for Zero-Shot MRI Reconstructioncited by 0
  2. 2026Consistent and Editable: A Balanced Framework for Text-Guided Video Editingcited by 0

Similar, not cited

Close in wording, no citation either way

  1. 2024Enhancing Diffusion Posterior Sampling for Inverse Problems by Integrating Crafted Measurements
  2. 2024Frequency-Guided Posterior Sampling for Diffusion-Based Image Restoration
  3. 2024Decoupled Data Consistency with Diffusion Purification for Image Restoration
  4. 2023Generative Diffusion Prior for Unified Image Restoration and Enhancement
  5. 2023A Unified Conditional Framework for Diffusion-based Image Restoration
  6. 2025Diffusion Restoration Adapter for Real-World Image Restoration
  7. 2025Exploiting the Exact Denoising Posterior Score in Training-Free Guidance of Diffusion Models
  8. 2022Denoising Diffusion Restoration Models