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Photo-realistic image restoration algorithms are typically evaluated by distortion measures (e.g., PSNR, SSIM) and by perceptual quality measures (e.g., FID, NIQE), where the desire is to attain the lowest possible distortion without compromising on perceptual quality.
Statistical Models
A. C. Davison · 2003
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Image quality assessment: from error visibility to structural similarity
Zhou Wang, A.C. Bovik, H.R. Sheikh, and E.P. Simoncelli · 2003
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Statistical and Computational Inverse Problems
Jari Kaipio and Erkki Somersalo · 2005
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Labeled Faces in the Wild: A Database forStudying Face Recognition in Unconstrained Environments
Gary B. Huang, Marwan Mattar, Tamara Berg, and Eric Learned-Miller · 2008
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Imagenet: A large-scale hierarchical image database
Jia Deng, Wei Dong, Richard Socher, Li-Jia Li, Kai Li, and Li Fei-Fei · 2009
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Making a “completely blind” image quality analyzer
Anish Mittal, Rajiv Soundararajan, and Alan C. Bovik · 2012
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Generative adversarial nets
Ian Goodfellow, Jean Pouget-Abadie, Mehdi Mirza, Bing Xu, David Warde-Farley, Sherjil Ozair, Aaron Courville, and Yoshua Bengio · 2014
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Auto-encoding variational bayes
Diederik P. Kingma and Max Welling · 2014
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Deep generative image models using a laplacian pyramid of adversarial networks
Emily L Denton, Soumith Chintala, arthur szlam, and Rob Fergus · 2015
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Let there be Color!: Joint End-to-end Learning of Global and Local Image Priors for Automatic Image Colorization with Simultaneous Classification
Satoshi Iizuka, Edgar Simo-Serra, and Hiroshi Ishikawa · 2016
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Improved techniques for training gans
Tim Salimans, Ian Goodfellow, Wojciech Zaremba, Vicki Cheung, Alec Radford, Xi Chen, and Xi Chen · 2016
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Rethinking the inception architecture for computer vision
Christian Szegedy, Vincent Vanhoucke, Sergey Ioffe, Jon Shlens, and Zbigniew Wojna · 2016
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Colorful image colorization
Richard Zhang, Phillip Isola, and Alexei A Efros · 2016
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Pixel recursive super resolution
Ryan Dahl, Mohammad Norouzi, and Jonathon Shlens · 2017
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Pixcolor: Pixel recursive colorization
Sergio Guadarrama, Ryan Dahl, David Bieber, Jonathon Shlens, Mohammad Norouzi, and Kevin Murphy · 2017
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Gans trained by a two time-scale update rule converge to a local nash equilibrium
Martin Heusel, Hubert Ramsauer, Thomas Unterthiner, Bernhard Nessler, and Sepp Hochreiter · 2017
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Image-to-image translation with conditional adversarial networks
Phillip Isola, Jun-Yan Zhu, Tinghui Zhou, and Alexei A Efros · 2017
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Photo-realistic single image super-resolution using a generative adversarial network
Christian Ledig, Lucas Theis, Ferenc Huszár, Jose Caballero, Andrew Cunningham, Alejandro Acosta, Andrew Aitken, Alykhan Tejani, Johannes Totz, Zehan Wang, and Wenzhe Shi · 2017
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Real-time user-guided image colorization with learned deep priors
Richard Zhang, Jun-Yan Zhu, Phillip Isola, Xinyang Geng, Angela S Lin, Tianhe Yu, and Alexei A Efros · 2017
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Demystifying MMD GANs
Mikołaj Bińkowski, Dougal J. Sutherland, Michael Arbel, and Arthur Gretton · 2018
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The perception-distortion tradeoff
Yochai Blau and Tomer Michaeli · 2018
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Progressive growing of GANs for improved quality, stability, and variation
Tero Karras, Timo Aila, Samuli Laine, and Jaakko Lehtinen · 2018
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Nima: Neural image assessment
Hossein Talebi and Peyman Milanfar · 2018
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Esrgan: Enhanced super-resolution generative adversarial networks
Xintao Wang, Ke Yu, Shixiang Wu, Jinjin Gu, Yihao Liu, Chao Dong, Yu Qiao, and Chen Change Loy · 2018
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The unreasonable effectiveness of deep features as a perceptual metric
Richard Zhang, Phillip Isola, Alexei A Efros, Eli Shechtman, and Oliver Wang · 2018
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Arcface: Additive angular margin loss for deep face recognition
Jiankang Deng, Jia Guo, Niannan Xue, and Stefanos Zafeiriou · 2019
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A style-based generator architecture for generative adversarial networks
Tero Karras, Samuli Laine, and Timo Aila · 2019
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Improved precision and recall metric for assessing generative models
Tuomas Kynkäänniemi, Tero Karras, Samuli Laine, Jaakko Lehtinen, and Timo Aila · 2019
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Decoupled weight decay regularization
Towards robust blind face restoration with codebook lookup transformer
Shangchen Zhou, Kelvin C.K. Chan, Chongyi Li, and Chen Change Loy · 2022
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Deep optimal transport: A practical algorithm for photo-realistic image restoration
Theo Adrai, Guy Ohayon, Michael Elad, and Tomer Michaeli · 2023
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Stochastic interpolants with data-dependent couplings
Michael S. Albergo, Mark Goldstein, Nicholas M. Boffi, Rajesh Ranganath, and Eric Vanden-Eijnden · 2023
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Building normalizing flows with stochastic interpolants
Michael Samuel Albergo and Eric Vanden-Eijnden · 2023
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A regularized conditional GAN for posterior sampling in image recovery problems
Matthew C Bendel, Rizwan Ahmad, and Philip Schniter · 2023
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Ilya Loshchilov and Frank Hutter · 2019
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High-fidelity performance metrics for generative models in pytorch, 2020
Anton Obukhov, Maximilian Seitzer, Po-Wei Wu, Semen Zhydenko, Jonathan Kyl, and Elvis Yu-Jing Lin · 2020
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A theory of the distortion-perception tradeoff in wasserstein space
Dror Freirich, Tomer Michaeli, and Ron Meir · 2021
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Stochastic image denoising by sampling from the posterior distribution
Bahjat Kawar, Gregory Vaksman, and Michael Elad · 2021
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Snips: Solving noisy inverse problems stochastically
Bahjat Kawar, Gregory Vaksman, and Michael Elad · 2021
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Swinir: Image restoration using swin transformer
Jingyun Liang, Jiezhang Cao, Guolei Sun, Kai Zhang, Luc Van Gool, and Radu Timofte · 2021
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High perceptual quality image denoising with a posterior sampling cgan
Guy Ohayon, Theo Adrai, Gregory Vaksman, Michael Elad, and Peyman Milanfar · 2021
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Diffusion posterior sampling for general noisy inverse problems
Hyungjin Chung, Jeongsol Kim, Michael Thompson Mccann, Marc Louis Klasky, and Jong Chul Ye · 2023
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Inversion by direct iteration: An alternative to denoising diffusion for image restoration
Mauricio Delbracio and Peyman Milanfar · 2023
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Bbdm: Image-to-image translation with brownian bridge diffusion models
Bo Li, Kaitao Xue, Bin Liu, and Yu-Kun Lai · 2023
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Flow matching for generative modeling
Yaron Lipman, Ricky T. Q. Chen, Heli Ben-Hamu, Maximilian Nickel, and Matthew Le · 2023
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Flow straight and fast: Learning to generate and transfer data with rectified flow
Xingchao Liu, Chengyue Gong, and qiang liu · 2023
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High-perceptual quality jpeg decoding via posterior sampling
Sean Man, Guy Ohayon, Theo Adrai, and Michael Elad · 2023
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GibbsDDRM: A partially collapsed Gibbs sampler for solving blind inverse problems with denoising diffusion restoration
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Pseudoinverse-guided diffusion models for inverse problems
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Exposing flaws of generative model evaluation metrics and their unfair treatment of diffusion models
George Stein, Jesse C. Cresswell, Rasa Hosseinzadeh, Yi Sui, Brendan Leigh Ross, Valentin Villecroze, Zhaoyan Liu, Anthony L. Caterini, Eric Taylor, and Gabriel Loaiza-Ganem · 2023
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Denoising diffusion models for plug-and-play image restoration
Yuanzhi Zhu, Kai Zhang, Jingyun Liang, Jiezhang Cao, Bihan Wen, Radu Timofte, and Luc Van Gool · 2023
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Towards real-world blind face restoration with generative diffusion prior
Xiaoxu Chen, Jingfan Tan, Tao Wang, Kaihao Zhang, Wenhan Luo, and Xiaochun Cao · 2024
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Katherine Crowson, Stefan Andreas Baumann, Alex Birch, Tanishq Mathew Abraham, Daniel Z Kaplan, and Enrico Shippole · 2024
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A survey on diffusion models for inverse problems
Giannis Daras, Hyungjin Chung, Chieh-Hsin Lai, Yuki Mitsufuji, Jong Chul Ye, Peyman Milanfar, Alexandros G. Dimakis, and Mauricio Delbracio · 2024
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Diffbir: Towards blind image restoration with generative diffusion prior
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Improving and generalizing flow-based generative models with minibatch optimal transport
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Difface: Blind face restoration with diffused error contraction
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Flowie: Efficient image enhancement via rectified flow
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