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Real-world image restoration is hampered by diverse degradations stemming from varying capture conditions, capture devices and post-processing pipelines.
Scikit-learn: Machine learning in Python
F. Pedregosa, G. Varoquaux, A. Gramfort, V. Michel, B. Thirion, O. Grisel, M. Blondel, P. Prettenhofer, R. Weiss, V. Dubourg, J. Vanderplas, A. Passos, D. Cournapeau, M. Brucher, M. Perrot, and E. Duchesnay · 2011
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Burst deblurring: Removing camera shake through fourier burst accumulation
Mauricio Delbracio and Guillermo Sapiro · 2015
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U-net: Convolutional networks for biomedical image segmentation, 2015
Olaf Ronneberger, Philipp Fischer, and Thomas Brox · 2015
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Massive online crowdsourced study of subjective and objective picture quality
Deepti Ghadiyaram and Alan C. Bovik · 2016
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Ntire 2017 challenge on single image super-resolution: Dataset and study
Eirikur Agustsson and Radu Timofte · 2017
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Model-agnostic meta-learning for fast adaptation of deep networks, 2017
Chelsea Finn, Pieter Abbeel, and Sergey Levine · 2017
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Enhanced deep residual networks for single image super-resolution
Bee Lim, Sanghyun Son, Heewon Kim, Seungjun Nah, and Kyoung Mu Lee · 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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Outrageously large neural networks: The sparsely-gated mixture-of-experts layer, 2017
Noam Shazeer, Azalia Mirhoseini, Krzysztof Maziarz, Andy Davis, Quoc Le, Geoffrey Hinton, and Jeff Dean · 2017
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Deep video deblurring for hand-held cameras
Shuochen Su, Mauricio Delbracio, Jue Wang, Guillermo Sapiro, Wolfgang Heidrich, and Oliver Wang · 2017
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A high-quality denoising dataset for smartphone cameras
Abdelrahman Abdelhamed, Stephen Lin, and Michael S. Brown · 2018
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JAX: composable transformations of Python+NumPy programs, 2018
James Bradbury, Roy Frostig, Peter Hawkins, Matthew James Johnson, Chris Leary, Dougal Maclaurin, George Necula, Adam Paszke, Jake VanderPlas, Skye Wanderman-Milne, and Qiao Zhang · 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, 2018
Xintao Wang, Ke Yu, Shixiang Wu, Jinjin Gu, Yihao Liu, Chao Dong, Chen Change Loy, Yu Qiao, and Xiaoou Tang · 2018
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Toward real-world single image super-resolution: A new benchmark and a new model
Jianrui Cai, Hui Zeng, Hongwei Yong, Zisheng Cao, and Lei Zhang · 2019
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Meta-sr: A magnification-arbitrary network for super-resolution, 2019
Xuecai Hu, Haoyuan Mu, Xiangyu Zhang, Zilei Wang, Tieniu Tan, and Jian Sun · 2019
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A style-based generator architecture for generative adversarial networks, 2019
Tero Karras, Samuli Laine, and Timo Aila · 2019
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Defocus deblurring using dual-pixel data
Abdullah Abuolaim and Michael S Brown · 2020
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Perceptual quality assessment of smartphone photography
Yuming Fang, Hanwei Zhu, Yan Zeng, Kede Ma, and Zhou Wang · 2020
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A brief review of domain adaptation, 2020
Abolfazl Farahani, Sahar Voghoei, Khaled Rasheed, and Hamid R. Arabnia · 2020
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Denoising diffusion probabilistic models, 2020
Jonathan Ho, Ajay Jain, and Pieter Abbeel · 2020
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Koniq-10k: An ecologically valid database for deep learning of blind image quality assessment
V. Hosu, H. Lin, T. Sziranyi, and D. Saupe · 2020
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The open images dataset v4: Unified image classification, object detection, and visual relationship detection at scale
Alina Kuznetsova, Hassan Rom, Neil Alldrin, Jasper Uijlings, Ivan Krasin, Jordi Pont-Tuset, Shahab Kamali, Stefan Popov, Matteo Malloci, Alexander Kolesnikov, Tom Duerig, and Vittorio Ferrari · 2020
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Component divide-and-conquer for real-world image super-resolution, 2020
Pengxu Wei, Ziwei Xie, Hannan Lu, Zongyuan Zhan, Qixiang Ye, Wangmeng Zuo, and Liang Lin · 2020
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Deblurring by realistic blurring, 2020
Kaihao Zhang, Wenhan Luo, Yiran Zhong, Lin Ma, Bjorn Stenger, Wei Liu, and Hongdong Li · 2020
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Pre-trained image processing transformer
Hanting Chen, Yunhe Wang, Tianyu Guo, Chang Xu, Yiping Deng, Zhenhua Liu, Siwei Ma, Chunjing Xu, Chao Xu, and Wen Gao · 2021
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Musiq: Multi-scale image quality transformer, 2021
Junjie Ke, Qifei Wang, Yilin Wang, Peyman Milanfar, and Feng Yang · 2021
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Swinir: Image restoration using swin transformer, 2021
Jingyun Liang, Jiezhang Cao, Guolei Sun, Kai Zhang, Luc Van Gool, and Radu Timofte · 2021
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Real-esrgan: Training real-world blind super-resolution with pure synthetic data
Xintao Wang, Liangbin Xie, Chao Dong, and Ying Shan · 2021
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Simple baselines for image restoration
Liangyu Chen, Xiaojie Chu, Xiangyu Zhang, and Jian Sun · 2022
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Classifier-free diffusion guidance, 2022
A comprehensive survey on test-time adaptation under distribution shifts, 2023
Jian Liang, Ran He, and Tieniu Tan · 2023
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Visual instruction tuning, 2023
Haotian Liu, Chunyuan Li, Qingyang Wu, and Yong Jae Lee · 2023
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Scalable diffusion models with transformers, 2023
William Peebles and Saining Xie · 2023
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Sdxl: Improving latent diffusion models for high-resolution image synthesis, 2023
Dustin Podell, Zion English, Kyle Lacey, Andreas Blattmann, Tim Dockhorn, Jonas Müller, Joe Penna, and Robin Rombach · 2023
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Promptir: Prompting for all-in-one image restoration
Vaishnav Potlapalli, Syed Waqas Zamir, Salman Khan, and Fahad Khan · 2023
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Multiscale structure guided diffusion for image deblurring, 2023
Mengwei Ren, Mauricio Delbracio, Hossein Talebi, Guido Gerig, and Peyman Milanfar · 2023
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Jonathan Ho and Tim Salimans · 2022
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Auto-encoding variational bayes, 2022
Diederik P Kingma and Max Welling · 2022
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All-In-One Image Restoration for Unknown Corruption
Boyun Li, Xiao Liu, Peng Hu, Zhongqin Wu, Jiancheng Lv, and Xi Peng · 2022
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Training language models to follow instructions with human feedback, 2022
Long Ouyang, Jeff Wu, Xu Jiang, Diogo Almeida, Carroll L. Wainwright, Pamela Mishkin, Chong Zhang, Sandhini Agarwal, Katarina Slama, Alex Ray, John Schulman, Jacob Hilton, Fraser Kelton, Luke Miller, Maddie Simens, Amanda Askell, Peter Welinder, Paul Christiano, Jan Leike, and Ryan Lowe · 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, 2022
Robin Rombach, Andreas Blattmann, Dominik Lorenz, Patrick Esser, and Björn Ommer · 2022
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Progressive distillation for fast sampling of diffusion models, 2022
Tim Salimans and Jonathan Ho · 2022
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Adversarial diffusion distillation, 2023
Axel Sauer, Dominik Lorenz, Andreas Blattmann, and Robin Rombach · 2023
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Exploring clip for assessing the look and feel of images
Jianyi Wang, Kelvin CK Chan, and Chen Change Loy · 2023
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Towards real-world burst image super-resolution: Benchmark and method, 2023
Pengxu Wei, Yujing Sun, Xingbei Guo, Chang Liu, Jie Chen, Xiangyang Ji, and Liang Lin · 2023
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Adding conditional control to text-to-image diffusion models, 2023
Lvmin Zhang, Anyi Rao, and Maneesh Agrawala · 2023
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Diffusion soup: Model merging for text-to-image diffusion models, 2024
Benjamin Biggs, Arjun Seshadri, Yang Zou, Achin Jain, Aditya Golatkar, Yusheng Xie, Alessandro Achille, Ashwin Swaminathan, and Stefano Soatto · 2024
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Restoreagent: Autonomous image restoration agent via multimodal large language models, 2024
Haoyu Chen, Wenbo Li, Jinjin Gu, Jingjing Ren, Sixiang Chen, Tian Ye, Renjing Pei, Kaiwen Zhou, Fenglong Song, and Lei Zhu · 2024
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Referring flexible image restoration, 2024
Runwei Guan, Rongsheng Hu, Zhuhao Zhou, Tianlang Xue, Ka Lok Man, Jeremy Smith, Eng Gee Lim, Weiping Ding, and Yutao Yue · 2024
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Autodir: Automatic all-in-one image restoration with latent diffusion, 2024
Yitong Jiang, Zhaoyang Zhang, Tianfan Xue, and Jinwei Gu · 2024
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Rich human feedback for text-to-image generation, 2024
Youwei Liang, Junfeng He, Gang Li, Peizhao Li, Arseniy Klimovskiy, Nicholas Carolan, Jiao Sun, Jordi Pont-Tuset, Sarah Young, Feng Yang, Junjie Ke, Krishnamurthy Dj Dvijotham, Katie Collins, Yiwen Luo, Yang Li, Kai J Kohlhoff, Deepak Ramachandran, and Vidhya Navalpakkam · 2024
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Diffbir: Towards blind image restoration with generative diffusion prior, 2024
Xinqi Lin, Jingwen He, Ziyan Chen, Zhaoyang Lyu, Bo Dai, Fanghua Yu, Wanli Ouyang, Yu Qiao, and Chao Dong · 2024
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Codi: Conditional diffusion distillation for higher-fidelity and faster image generation
Kangfu Mei, Mauricio Delbracio, Hossein Talebi, Zhengzhong Tu, Vishal M. Patel, and Peyman Milanfar · 2024
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Spire: Semantic prompt-driven image restoration, 2024
Chenyang Qi, Zhengzhong Tu, Keren Ye, Mauricio Delbracio, Peyman Milanfar, Qifeng Chen, and Hossein Talebi · 2024
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Xpsr: Cross-modal priors for diffusion-based image super-resolution, 2024
Yunpeng Qu, Kun Yuan, Kai Zhao, Qizhi Xie, Jinhua Hao, Ming Sun, and Chao Zhou · 2024
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Exploiting diffusion prior for real-world image super-resolution
Jianyi Wang, Zongsheng Yue, Shangchen Zhou, Kelvin C.K. Chan, and Chen Change Loy · 2024
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Seesr: Towards semantics-aware real-world image super-resolution, 2024
Rongyuan Wu, Tao Yang, Lingchen Sun, Zhengqiang Zhang, Shuai Li, and Lei Zhang · 2024
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Pixel-aware stable diffusion for realistic image super-resolution and personalized stylization
Tao Yang, Rongyuan Wu, Peiran Ren, Xuansong Xie, , and Lei Zhang · 2024
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The emergence of reproducibility and generalizability in diffusion models, 2024
Huijie Zhang, Jinfan Zhou, Yifu Lu, Minzhe Guo, Peng Wang, Liyue Shen, and Qing Qu · 2024
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Deployment prior injection for run-time calibratable object detection, 2024
Mo Zhou, Yiding Yang, Haoxiang Li, Vishal M. Patel, and Gang Hua · 2024
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