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Diffusion Probabilistic Models (DPMs) have recently been employed for image deblurring, formulated as an image-conditioned generation process that maps Gaussian noise to the high-quality image, conditioned on the blurry input.
Removing camera shake from a single photograph
Rob Fergus, Barun Singh, Aaron Hertzmann, Sam T Roweis, and William T Freeman · 2006
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Blind deconvolution using a normalized sparsity measure
Dilip Krishnan, Terence Tay, and Rob Fergus · 2011
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Efficient marginal likelihood optimization in blind deconvolution
Anat Levin, Yair Weiss, Fredo Durand, and William T Freeman · 2011
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Making a “completely blind” image quality analyzer
Anish Mittal, Rajiv Soundararajan, and Alan C Bovik · 2012
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Unnatural l0 sparse representation for natural image deblurring
Li Xu, Shicheng Zheng, and Jiaya Jia · 2013
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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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Adam: A method for stochastic optimization
Diederik P Kingma and Jimmy Ba · 2014
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Blind deblurring using internal patch recurrence
Tomer Michaeli and Michal Irani · 2014
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Deblurring text images via l0-regularized intensity and gradient prior
Jinshan Pan, Zhe Hu, Zhixun Su, and Ming-Hsuan Yang · 2014
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U-net: Convolutional networks for biomedical image segmentation
Olaf Ronneberger, Philipp Fischer, and Thomas Brox · 2015
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Deep unsupervised learning using nonequilibrium thermodynamics
Jascha Sohl-Dickstein, Eric Weiss, Niru Maheswaranathan, and Surya Ganguli · 2015
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Super-resolution with deep convolutional sufficient statistics
Joan Bruna, Pablo Sprechmann, and Yann LeCun · 2016
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Perceptual losses for real-time style transfer and super-resolution
Justin Johnson, Alexandre Alahi, and Li Fei-Fei · 2016
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Blind image deblurring using dark channel prior
Jinshan Pan, Deqing Sun, Hanspeter Pfister, and Ming-Hsuan Yang · 2016
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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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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, et al · 2017
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Deep multi-scale convolutional neural network for dynamic scene deblurring
Seungjun Nah, Tae Hyun Kim, and Kyoung Mu Lee · 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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Cycada: Cycle-consistent adversarial domain adaptation
Judy Hoffman, Eric Tzeng, Taesung Park, Jun-Yan Zhu, Phillip Isola, Kate Saenko, Alexei Efros, and Trevor Darrell · 2018
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Normalized blind deconvolution
Meiguang Jin, Stefan Roth, and Paolo Favaro · 2018
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Deblurgan: Blind motion deblurring using conditional adversarial networks
Orest Kupyn, Volodymyr Budzan, Mykola Mykhailych, Dmytro Mishkin, and Jiri Matas · 2018
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Maintaining natural image statistics with the contextual loss
Roey Mechrez, Itamar Talmi, Firas Shama, and Lihi Zelnik-Manor · 2018
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The contextual loss for image transformation with non-aligned data
Roey Mechrez, Itamar Talmi, and Lihi Zelnik-Manor · 2018
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Which training methods for gans do actually converge?
Lars Mescheder, Andreas Geiger, and Sebastian Nowozin · 2018
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Recovering realistic texture in image super-resolution by deep spatial feature transform
Xintao Wang, Ke Yu, Chao Dong, and Chen Change Loy · 2018
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Dynamic scene deblurring using spatially variant recurrent neural networks
Jiawei Zhang, Jinshan Pan, Jimmy Ren, Yibing Song, Linchao Bao, Rynson WH Lau, and Ming-Hsuan Yang · 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
Earlier work this paper cites.
The unreasonable effectiveness of deep features as a perceptual metric
Richard Zhang, Phillip Isola, Alexei A. Efros, Eli Shechtman, and Oliver Wang · 2018
Earlier work this paper cites.
Efficient blind deblurring under high noise levels
Jérémy Anger, Mauricio Delbracio, and Gabriele Facciolo · 2019
Earlier work this paper cites.
Deblurgan-v2: Deblurring (orders-of-magnitude) faster and better
Orest Kupyn, Tetiana Martyniuk, Junru Wu, and Zhangyang Wang · 2019
Earlier work this paper cites.
Unsupervised domain-specific deblurring via disentangled representations
Boyu Lu, Jun-Cheng Chen, and Rama Chellappa · 2019
Earlier work this paper cites.
Ntire 2019 challenge on video deblurring and super-resolution: Dataset and study
Seungjun Nah, Sungyong Baik, Seokil Hong, Gyeongsik Moon, Sanghyun Son, Radu Timofte, and Kyoung Mu Lee · 2019
Earlier work this paper cites.
Human-aware motion deblurring
Ziyi Shen, Wenguan Wang, Jianbing Shen, Haibin Ling, Tingfa Xu, and Ling Shao · 2019
Earlier work this paper cites.
Generative modeling by estimating gradients of the data distribution
Yang Song and Stefano Ermon · 2019
Earlier work this paper cites.
Deep stacked hierarchical multi-patch network for image deblurring
Hongguang Zhang, Yuchao Dai, Hongdong Li, and Piotr Koniusz · 2019
Cited alongside, same era.
Zoom to learn, learn to zoom
Xuaner Zhang, Qifeng Chen, Ren Ng, and Vladlen Koltun · 2019
Cited alongside, same era.
Spatio-temporal filter adaptive network for video deblurring
Shangchen Zhou, Jiawei Zhang, Jinshan Pan, Haozhe Xie, Wangmeng Zuo, and Jimmy Ren · 2019
Cited alongside, same era.
Denoising diffusion probabilistic models
Jonathan Ho, Ajay Jain, and Pieter Abbeel · 2020
Cited alongside, same era.
Jim Nilsson and Tomas Akenine-Möller · 2020
Cited alongside, same era.
Single image super-resolution via a holistic attention network
Ben Niu, Weilei Wen, Wenqi Ren, Xiangde Zhang, Lianping Yang, Shuzhen Wang, Kaihao Zhang, Xiaochun Cao, and Haifeng Shen · 2020
Soft diffusion: Score matching for general corruptions
Giannis Daras, Mauricio Delbracio, Hossein Talebi, Alexandros G Dimakis, and Peyman Milanfar · 2022
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Genie: Higher-order denoising diffusion solvers
Tim Dockhorn, Arash Vahdat, and Karsten Kreis · 2022
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Jonathan Ho, Tim Salimans, Alexey Gritsenko, William Chan, Mohammad Norouzi, and David J Fleet · 2022
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Emiel Hoogeboom and Tim Salimans · 2022
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Xydeblur: Divide and conquer for single image deblurring
Seo-Won Ji, Jeongmin Lee, Seung-Wook Kim, Jun-Pyo Hong, Seung-Jin Baek, Seung-Won Jung, and Sung-Jea Ko · 2022
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Cited alongside, same era.
Real-world blur dataset for learning and benchmarking deblurring algorithms
Jaesung Rim, Haeyun Lee, Jucheol Won, and Sunghyun Cho · 2020
Cited alongside, same era.
Domain adaptation for image dehazing
Yuanjie Shao, Lerenhan Li, Wenqi Ren, Changxin Gao, and Nong Sang · 2020
Cited alongside, same era.
Improved techniques for training score-based generative models
Yang Song and Stefano Ermon · 2020
Cited alongside, same era.
Spatially-attentive patch-hierarchical network for adaptive motion deblurring
Maitreya Suin, Kuldeep Purohit, and A. N. Rajagopalan · 2020
Cited alongside, same era.
Learning enriched features for real image restoration and enhancement
Syed Waqas Zamir, Aditya Arora, Salman Khan, Munawar Hayat, Fahad Shahbaz Khan, Ming-Hsuan Yang, and Ling Shao · 2020
Cited alongside, same era.
Deblurring by realistic blurring
Kaihao Zhang, Wenhan Luo, Yiran Zhong, Lin Ma, Bjorn Stenger, Wei Liu, and Hongdong Li · 2020
Cited alongside, same era.
Closest in time.
Elucidating the design space of diffusion-based generative models
Tero Karras, Miika Aittala, Timo Aila, and Samuli Laine · 2022
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Denoising diffusion restoration models
Bahjat Kawar, Michael Elad, Stefano Ermon, and Jiaming Song · 2022
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Enhancing diffusion-based image synthesis with robust classifier guidance
Bahjat Kawar, Roy Ganz, and Michael Elad · 2022
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Jpeg artifact correction using denoising diffusion restoration models
Bahjat Kawar, Jiaming Song, Stefano Ermon, and Michael Elad · 2022
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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 · 2022
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Learning degradation representations for image deblurring
Dasong Li, Yi Zhang, Ka Chun Cheung, Xiaogang Wang, Hongwei Qin, and Hongsheng Li · 2022
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Srdiff: Single image super-resolution with diffusion probabilistic models
Haoying Li, Yifan Yang, Meng Chang, Shiqi Chen, Huajun Feng, Zhihai Xu, Qi Li, and Yueting Chen · 2022
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Efficient spatially sparse inference for conditional gans and diffusion models
Muyang Li, Ji Lin, Chenlin Meng, Stefano Ermon, Song Han, and Jun-Yan Zhu · 2022
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Dpm-solver: A fast ode solver for diffusion probabilistic model sampling in around 10 steps
Cheng Lu, Yuhao Zhou, Fan Bao, Jianfei Chen, Chongxuan Li, and Jun Zhu · 2022
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Accelerating score-based generative models with preconditioned diffusion sampling
Hengyuan Ma, Li Zhang, Xiatian Zhu, and Jianfeng Feng · 2022
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On distillation of guided diffusion models
Chenlin Meng, Ruiqi Gao, Diederik P Kingma, Stefano Ermon, Jonathan Ho, and Tim Salimans · 2022
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Clean images are hard to reblur: Exploiting the ill-posed inverse task for dynamic scene deblurring
Seungjun Nah, Sanghyun Son, Jaerin Lee, and Kyoung Mu Lee · 2022
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Hierarchical text-conditional image generation with clip latents
Aditya Ramesh, Prafulla Dhariwal, Alex Nichol, Casey Chu, and Mark Chen · 2022
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Realistic blur synthesis for learning image deblurring
Jaesung Rim, Geonung Kim, Jungeon Kim, Junyong Lee, Seungyong Lee, and Sunghyun Cho · 2022
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High-resolution image synthesis with latent diffusion models
Robin Rombach, Andreas Blattmann, Dominik Lorenz, Patrick Esser, and Björn Ommer · 2022
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High-resolution image synthesis with latent diffusion models
Robin Rombach, Andreas Blattmann, Dominik Lorenz, Patrick Esser, and Björn Ommer · 2022
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Dreambooth: Fine tuning text-to-image diffusion models for subject-driven generation
Nataniel Ruiz, Yuanzhen Li, Varun Jampani, Yael Pritch, Michael Rubinstein, and Kfir Aberman · 2022
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Palette: Image-to-image diffusion models
Chitwan Saharia, William Chan, Huiwen Chang, Chris Lee, Jonathan Ho, Tim Salimans, David Fleet, and Mohammad Norouzi · 2022
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Photorealistic text-to-image diffusion models with deep language understanding
Chitwan Saharia, William Chan, Saurabh Saxena, Lala Li, Jay Whang, Emily Denton, Seyed Kamyar Seyed Ghasemipour, Burcu Karagol Ayan, S Sara Mahdavi, Rapha Gontijo Lopes, et al · 2022
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Image super-resolution via iterative refinement
Chitwan Saharia, Jonathan Ho, William Chan, Tim Salimans, David J Fleet, and Mohammad Norouzi · 2022
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Diffusion art or digital forgery? investigating data replication in diffusion models
Gowthami Somepalli, Vasu Singla, Micah Goldblum, Jonas Geiping, and Tom Goldstein · 2022
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Stripformer: Strip transformer for fast image deblurring
Fu-Jen Tsai, Yan-Tsung Peng, Yen-Yu Lin, Chung-Chi Tsai, and Chia-Wen Lin · 2022
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Maxim: Multi-axis mlp for image processing
Zhengzhong Tu, Hossein Talebi, Han Zhang, Feng Yang, Peyman Milanfar, Alan Bovik, and Yinxiao Li · 2022
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Uformer: A general u-shaped transformer for image restoration
Zhendong Wang, Xiaodong Cun, Jianmin Bao, Wengang Zhou, Jianzhuang Liu, and Houqiang Li · 2022
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Deblurring via stochastic refinement
Jay Whang, Mauricio Delbracio, Hossein Talebi, Chitwan Saharia, Alexandros G Dimakis, and Peyman Milanfar · 2022
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Tackling the generative learning trilemma with denoising diffusion GANs
Zhisheng Xiao, Karsten Kreis, and Arash Vahdat · 2022
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Restormer: Efficient transformer for high-resolution image restoration
Syed Waqas Zamir, Aditya Arora, Salman Khan, Munawar Hayat, Fahad Shahbaz Khan, and Ming-Hsuan Yang · 2022
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Lednet: Joint low-light enhancement and deblurring in the dark
Shangchen Zhou, Chongyi Li, and Chen Change Loy · 2022
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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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Adding conditional control to text-to-image diffusion models
Lvmin Zhang and Maneesh Agrawala · 2023
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