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Plug-and-Play methods constitute a class of iterative algorithms for imaging problems where regularization is performed by an off-the-shelf denoiser.
Block coordinate regularization by denoising
Yu Sun, Jiaming Liu, and Ulugbek S Kamilov · 1905
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Proximité et dualité dans un espace hilbertien
Jean-Jacques Moreau · 1965
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Nonlinear total variation based noise removal algorithms
Leonid I Rudin, Stanley Osher, and Emad Fatemi · 1992
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Nonlinear image recovery with half-quadratic regularization
Donald Geman and Chengda Yang · 1995
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A database of human segmented natural images and its application to evaluating segmentation algorithms and measuring ecological statistics
D. Martin, C. Fowlkes, D. Tal, and J. Malik · 2001
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Gradient-based algorithms with applications to signal recovery
Amir Beck and Marc Teboulle · 2009
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Understanding and evaluating blind deconvolution algorithms
Anat Levin, Yair Weiss, Fredo Durand, and William T Freeman · 2009
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A Wavelet Tour of Signal Processing, The Sparse Way
Stéphane Mallat · 2009
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Proximal alternating minimization and projection methods for nonconvex problems: An approach based on the kurdyka-łojasiewicz inequality
Hédy Attouch, Jérôme Bolte, Patrick Redont, and Antoine Soubeyran · 2010
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Characterizations of łojasiewicz inequalities: subgradient flows, talweg, convexity
Jérôme Bolte, Aris Daniilidis, Olivier Ley, and Laurent Mazet · 2010
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Convex Analysis and Monotone Operator Theory in Hilbert Spaces
H. H. Bauschke and P. L. Combettes · 2011
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Proximal splitting methods in signal processing
Patrick L. Combettes and Jean-Christophe Pesquet · 2011
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Tweedie’s formula and selection bias
Bradley Efron · 2011
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From learning models of natural image patches to whole image restoration
Daniel Zoran and Yair Weiss · 2011
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Convergence of descent methods for semi-algebraic and tame problems: proximal algorithms, forward–backward splitting, and regularized gauss–seidel methods
Hedy Attouch, Jérôme Bolte, and Benar Fux Svaiter · 2013
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Plug-and-play priors for model based reconstruction
Singanallur V Venkatakrishnan, Charles A Bouman, and Brendt Wohlberg · 2013
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ipiano: Inertial proximal algorithm for nonconvex optimization
Peter Ochs, Yunjin Chen, Thomas Brox, and Thomas Pock · 2014
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Fast first-order methods for composite convex optimization with backtracking
Katya Scheinberg, Donald Goldfarb, and Xi Bai · 2014
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Accelerated proximal gradient methods for nonconvex programming
Huan Li and Zhouchen Lin · 2015
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Plug-and-play ADMM for image restoration: Fixed-point convergence and applications
Stanley H Chan, Xiran Wang, and Omar A Elgendy · 2016
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Trainable nonlinear reaction diffusion: A flexible framework for fast and effective image restoration
Yunjin Chen and Thomas Pock · 2016
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Plug-and-play priors for bright field electron tomography and sparse interpolation
Suhas Sreehari, S Venkat Venkatakrishnan, Brendt Wohlberg, Gregery T Buzzard, Lawrence F Drummy, Jeffrey P Simmons, and Charles A Bouman · 2016
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Fast single image super-resolution using a new analytical solution for ℓ 2 − ℓ 2 \ell_{2}-\ell_{2} problems
Ningning Zhao, Qi Wei, Adrian Basarab, Nicolas Dobigeon, Denis Kouamé, and Jean-Yves Tourneret · 2016
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Ntire 2017 challenge on single image super-resolution: Dataset and study
Eirikur Agustsson and Radu Timofte · 2017
Cited alongside, same era.
First-order methods in optimization
Amir Beck · 2017
Cited alongside, same era.
Image restoration using autoencoding priors
Siavash Arjomand Bigdeli and Matthias Zwicker · 2017
Cited alongside, same era.
Deep mean-shift priors for image restoration
Siavash Arjomand Bigdeli, Meiguang Jin, Paolo Favaro, and Matthias Zwicker · 2017
Cited alongside, same era.
Enhanced deep residual networks for single image super-resolution
Bee Lim, Sanghyun Son, Heewon Kim, Seungjun Nah, and Kyoung Mu Lee · 2017
Cited alongside, same era.
Plug-and-play ista converges with kernel denoisers
Ruturaj G Gavaskar and Kunal N Chaudhury · 2020
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Denoising diffusion probabilistic models
Jonathan Ho, Ajay Jain, and Pieter Abbeel · 2020
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Solving linear inverse problems using the prior implicit in a denoiser
Zahra Kadkhodaie and Eero Peter Simoncelli · 2020
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Rare: Image reconstruction using deep priors learned without groundtruth
Jiaming Liu, Yu Sun, Cihat Eldeniz, Weijie Gan, Hongyu An, and Ulugbek S Kamilov · 2020
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Yu Sun, Jiaming Liu, Yiran Sun, Brendt Wohlberg, and Ulugbek S Kamilov · 2020
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Kede Ma, Zhengfang Duanmu, Qingbo Wu, Zhou Wang, Hongwei Yong, Hongliang Li, and Lei Zhang · 2017
Cited alongside, same era.
Learning proximal operators: Using denoising networks for regularizing inverse imaging problems
Tim Meinhardt, Michael Moller, Caner Hazirbas, and Daniel Cremers · 2017
Cited alongside, same era.
The little engine that could: Regularization by denoising (red)
Yaniv Romano, Michael Elad, and Peyman Milanfar · 2017
Cited alongside, same era.
Plug-and-play unplugged: Optimization-free reconstruction using consensus equilibrium
Gregery T Buzzard, Stanley H Chan, Suhas Sreehari, and Charles A Bouman · 2018
Cited alongside, same era.
Epll: an image denoising method using a gaussian mixture model learned on a large set of patches
Samuel Hurault, Thibaud Ehret, and Pablo Arias · 2018
Cited alongside, same era.
Adversarial regularizers in inverse problems
Sebastian Lunz, Ozan Öktem, and Carola-Bibiane Schönlieb · 2018
Cited alongside, same era.
prdeep: robust phase retrieval with a flexible deep network
Christopher Metzler, Phillip Schniter, Ashok Veeraraghavan, et al · 2018
Cited alongside, same era.
Building firmly nonexpansive convolutional neural networks
Matthieu Terris, Audrey Repetti, Jean-Christophe Pesquet, and Yves Wiaux · 2020
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Tuning-free plug-and-play proximal algorithm for inverse imaging problems
Kaixuan Wei, Angelica Aviles-Rivero, Jingwei Liang, Ying Fu, Carola-Bibiane Schönlieb, and Hua Huang · 2020
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Provable convergence of plug-and-play priors with mmse denoisers
Xiaojian Xu, Yu Sun, Jiaming Liu, Brendt Wohlberg, and Ulugbek S Kamilov · 2020
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Plug-and-play algorithms for large-scale snapshot compressive imaging
Xin Yuan, Yang Liu, Jinli Suo, and Qionghai Dai · 2020
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Learning lipschitz-controlled activation functions in neural networks for plug-and-play image reconstruction methods
Pakshal Bohra, Alexis Goujon, Dimitris Perdios, Sébastien Emery, and Michael Unser · 2021
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Regularization by denoising via fixed-point projection (RED-PRO)
Regev Cohen, Michael Elad, and Peyman Milanfar · 2021
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On plug-and-play regularization using linear denoisers
Ruturaj G Gavaskar, Chirayu D Athalye, and Kunal N Chaudhury · 2021
Closest in time.
Solving inverse problems by joint posterior maximization with autoencoding prior
Mario González, Andrés Almansa, and Pauline Tan · 2021
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Convolutional proximal neural networks and plug-and-play algorithms
Johannes Hertrich, Sebastian Neumayer, and Gabriele Steidl · 2021
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Bayesian imaging using plug & play priors: when langevin meets tweedie
Rémi Laumont, Valentin De Bortoli, Andrés Almansa, Julie Delon, Alain Durmus, and Marcelo Pereyra · 2021
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Recovery analysis for plug-and-play priors using the restricted eigenvalue condition
Jiaming Liu, M Salman Asif, Brendt Wohlberg, and Ulugbek S Kamilov · 2021
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Fixed-point and objective convergence of plug-and-play algorithms
Pravin Nair, Ruturaj Girish Gavaskar, and Kunal Narayan Chaudhury · 2021
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Learning maximally monotone operators for image recovery
Jean-Christophe Pesquet, Audrey Repetti, Matthieu Terris, and Yves Wiaux · 2021
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Learning local regularization for variational image restoration
Jean Prost, Antoine Houdard, Andrés Almansa, and Nicolas Papadakis · 2021
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Should EBMs model the energy or the score?
Tim Salimans and Jonathan Ho · 2021
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Scalable plug-and-play admm with convergence guarantees
Yu Sun, Zihui Wu, Xiaojian Xu, Brendt Wohlberg, and Ulugbek S Kamilov · 2021
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Plug-and-play image restoration with deep denoiser prior
Kai Zhang, Yawei Li, Wangmeng Zuo, Lei Zhang, Luc Van Gool, and Radu Timofte · 2021
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