mlsanityData to 7 Oct 2026

Plug-and-Play Priors as a Score-Based Method

arXiv 2412.11108 ↗First posted 15 Dec 2024eess.IV cs.CVcited by 5

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Abstract (arXiv)

Plug-and-play (PnP) methods are extensively used for solving imaging inverse problems by integrating physical measurement models with pre-trained deep denoisers as priors. Score-based diffusion models (SBMs) have recently emerged as a powerful framework for image generation by training deep denoisers to represent the score of the image prior. While both PnP and SBMs use deep denoisers, the score-based nature of PnP is unexplored in the literature due to its distinct origins rooted in proximal optimization. This letter introduces a novel view of PnP as a score-based method, a perspective that enables the re-use of powerful SBMs within classical PnP algorithms without retraining. We present a set of mathematical relationships for adapting popular SBMs as priors within PnP. We show that this approach enables a direct comparison between PnP and SBM-based reconstruction methods using the same neural network as the prior. Code is available at https://github.com/wustl-cig/score_pnp.

Key facts. Cited by 5 papers in the map (data through 7 Oct 2026). Builds on 28 of its 40 references that are in the map. First posted on arXiv 15 Dec 2024.

Builds on

28 of 40 references.

References · 28

  1. 2020Denoising Diffusion Probabilistic Modelscited by 20,851
  2. 2018The Unreasonable Effectiveness of Deep Features as a Perceptual Metriccited by 11,029
  3. 2020Score-Based Generative Modeling through Stochastic Differential Equationscited by 8,964
  4. 2021Diffusion Models Beat GANs on Image Synthesiscited by 8,185
  5. 2019Generative Modeling by Estimating Gradients of the Data Distributioncited by 4,067
  6. 2017Enhanced Deep Residual Networks for Single Image Super-Resolutioncited by 1,543
  7. 2022Diffusion Posterior Sampling for General Noisy Inverse Problemscited by 1,375
  8. 2016Beyond a Gaussian Denoiser: Residual Learning of Deep CNN for Image Denoisingcited by 1,352
  9. 2020Plug-and-Play Image Restoration with Deep Denoiser Priorcited by 467
  10. 2023Denoising Diffusion Models for Plug-and-Play Image Restorationcited by 335
  11. 2016The Little Engine that Could: Regularization by Denoising (RED)cited by 303
  12. 2016Plug-and-Play ADMM for Image Restoration: Fixed Point Convergence and Applicationscited by 244
16 more
  1. 2022Diffusion models as plug-and-play priorscited by 230
  2. 2019Plug-and-Play Methods Provably Converge with Properly Trained Denoiserscited by 197
  3. 2021Gradient Step Denoiser for convergent Plug-and-Playcited by 107
  4. 2021Bayesian imaging using Plug & Play priors: when Langevin meets Tweediecited by 96
  5. 2024Principled Probabilistic Imaging using Diffusion Models as Plug-and-Play Priorscited by 93
  6. 2022Proximal Denoiser for Convergent Plug-and-Play Optimization with Nonconvex Regularizationcited by 79
  7. 2019Plug and play methods for magnetic resonance imaging (long version)cited by 75
  8. 2022DOLCE: A Model-Based Probabilistic Diffusion Framework for Limited-Angle CT Reconstructioncited by 73
  9. 2024Provably Robust Score-Based Diffusion Posterior Sampling for Plug-and-Play Image Reconstructioncited by 73
  10. 2018An Online Plug-and-Play Algorithm for Regularized Image Reconstructioncited by 70
  11. 2023Provable Probabilistic Imaging using Score-Based Generative Priorscited by 51
  12. 2020Scalable Plug-and-Play ADMM with Convergence Guaranteescited by 49
  13. 2020Provable Convergence of Plug-and-Play Priors with MMSE denoiserscited by 39
  14. 2023Generative Plug and Play: Posterior Sampling for Inverse Problemscited by 24
  15. 2023Prior Mismatch and Adaptation in PnP-ADMM with a Nonconvex Convergence Analysiscited by 10
  16. 2024Regularization by denoising: Bayesian model and Langevin-within-split Gibbs samplingcited by 9

Built on by

Cited by year (2026 to 7 Oct)

Citing papers per year: 2025: 2; 2026: 3.

5 papers.

  1. 2025PnP-CM: Consistency Models as Plug-and-Play Priors for Inverse Problemscited by 4
  2. 2026Stochastic Generative Plug-and-Play Priorscited by 3
  3. 2025Deep Parameter Interpolation for Scalar Conditioningcited by 1
  4. 2026Bridging data-driven priors via the score function for posterior sampling -- Comparative review and experimental studycited by 0
  5. 2026Toward a Foundation Plug-and-Play Prior for Computed Tomography Reconstruction via a Multimodal Diffusion Modelcited by 0

Similar, not cited

Close in wording, no citation either way

  1. 2025Plug-and-Play Posterior Sampling for Blind Inverse Problems
  2. 2024PnP-Flow: Plug-and-Play Image Restoration with Flow Matching
  3. 2024Evaluating the Posterior Sampling Ability of Plug&Play Diffusion Methods in Sparse-View CT
  4. 2025Plug-and-play Diffusion Models for Image Compressive Sensing with Data Consistency Projection
  5. 2023Score-based Diffusion Models for Bayesian Image Reconstruction
  6. 2026Beyond MMSE: Enhancing PnP Restoration with ProxiMAP
  7. 2024Plug-and-Play image restoration with Stochastic deNOising REgularization
  8. 2023Score-Based Diffusion Models as Principled Priors for Inverse Imaging