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Existing image super-resolution (SR) techniques often fail to generalize effectively in complex real-world settings due to the significant divergence between training data and practical scenarios.
Real-esrgan: Training real-world blind super-resolution with pure synthetic data
Xintao Wang, Liangbin Xie, Chao Dong, and Ying Shan · 1914
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Restoration of a single superresolution image from several blurred, noisy, and undersampled measured images
Michael Elad and Arie Feuer · 1997
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Eigenface-domain super-resolution for face recognition
Bahadir K Gunturk, Aziz Umit Batur, Yucel Altunbasak, Monson H Hayes, and Russell M Mersereau · 2003
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Image quality assessment: from error visibility to structural similarity
Zhou Wang, Alan C Bovik, Hamid R Sheikh, and Eero P Simoncelli · 2004
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Scope of validity of psnr in image/video quality assessment
Quan Huynh-Thu and Mohammed Ghanbari · 2008
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Accelerating large-scale data exploration through data diffusion
Ioan Raicu, Yong Zhao, Ian T Foster, and Alex Szalay · 2008
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Accelerating the super-resolution convolutional neural network
Chao Dong, Chen Change Loy, and Xiaoou Tang · 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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Ntire 2017 challenge on single image super-resolution: Dataset and study
Eirikur Agustsson and Radu Timofte · 2017
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In defense of the triplet loss for person re-identification
Alexander Hermans, Lucas Beyer, and Bastian Leibe · 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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Dslr-quality photos on mobile devices with deep convolutional networks
Andrey Ignatov, Nikolay Kobyshev, Radu Timofte, Kenneth Vanhoey, and Luc Van Gool · 2017
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To learn image super-resolution, use a gan to learn how to do image degradation first
Adrian Bulat, Jing Yang, and Georgios Tzimiropoulos · 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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Unsupervised image super-resolution using cycle-in-cycle generative adversarial networks
Yuan Yuan, Siyuan Liu, Jiawei Zhang, Yongbing Zhang, Chao Dong, and Liang Lin · 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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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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Camera lens super-resolution
Chang Chen, Zhiwei Xiong, Xinmei Tian, Zheng-Jun Zha, and Feng Wu · 2019
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Benchmarking neural network robustness to common corruptions and perturbations
Dan Hendrycks and Thomas Dietterich · 2019
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Unsupervised learning for real-world super-resolution
Andreas Lugmayr, Martin Danelljan, and Radu Timofte · 2019
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Aim 2019 challenge on real-world image super-resolution: Methods and results
Andreas Lugmayr, Martin Danelljan, Radu Timofte, Manuel Fritsche, Shuhang Gu, Kuldeep Purohit, Praveen Kandula, Maitreya Suin, AN Rajagoapalan, Nam Hyung Joon, et al · 2019
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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
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Gradient image super-resolution for low-resolution image recognition
Dewan Fahim Noor, Yue Li, Zhu Li, Shuvra Bhattacharyya, and George York · 2019
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Generating diverse high-fidelity images with vq-vae-2, 2019
Ali Razavi, Aaron van den Oord, and Oriol Vinyals · 2019
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Image quality assessment: Unifying structure and texture similarity
Keyan Ding, Kede Ma, Shiqi Wang, and Eero P Simoncelli · 2020
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Denoising diffusion probabilistic models
Jonathan Ho, Ajay Jain, and Pieter Abbeel · 2020
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Unfolding the alternating optimization for blind super resolution
Yan Huang, Shang Li, Liang Wang, Tieniu Tan, et al · 2020
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Real-world super-resolution via kernel estimation and noise injection
Xiaozhong Ji, Yun Cao, Ying Tai, Chengjie Wang, Jilin Li, and Feiyue Huang · 2020
Blind image super-resolution: A survey and beyond
Anran Liu, Yihao Liu, Jinjin Gu, Yu Qiao, and Chao Dong · 2022
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Metric learning based interactive modulation for real-world super-resolution
Chong Mou, Yanze Wu, Xintao Wang, Chao Dong, Jian Zhang, and Ying Shan · 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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Generating high fidelity data from low-density regions using diffusion models
Vikash Sehwag, Caner Hazirbas, Albert Gordo, Firat Ozgenel, and Cristian Canton · 2022
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Efficient test-time adaptation for super-resolution with second-order degradation and reconstruction
Zeshuai Deng, Zhuokun Chen, Shuaicheng Niu, Thomas Li, Bohan Zhuang, and Mingkui Tan · 2023
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Ntire 2020 challenge on real-world image super-resolution: Methods and results
Andreas Lugmayr, Martin Danelljan, and Radu Timofte · 2020
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Unpaired image super-resolution using pseudo-supervision
Shunta Maeda · 2020
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Cumulative rain density sensing network for single image derain
Long Peng, Aiwen Jiang, Qiaosi Yi, and Mingwen Wang · 2020
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Deep learning for image super-resolution: A survey
Zhihao Wang, Jian Chen, and Steven CH Hoi · 2020
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Component divide-and-conquer for real-world image super-resolution
Pengxu Wei, Ziwei Xie, Hannan Lu, Zongyuan Zhan, Qixiang Ye, Wangmeng Zuo, and Liang Lin · 2020
Cited alongside, same era.
Degradation model learning for real-world single image super-resolution
Jin Xiao, Hongwei Yong, and Lei Zhang · 2020
Cited alongside, same era.
Yawei Li, Yulun Zhang, Radu Timofte, Luc Van Gool, Lei Yu, Youwei Li, Xinpeng Li, Ting Jiang, Qi Wu, Mingyan Han, et al · 2023
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Evaluating the generalization ability of super-resolution networks
Yihao Liu, Hengyuan Zhao, Jinjin Gu, Yu Qiao, and Chao Dong · 2023
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Tf-icon: Diffusion-based training-free cross-domain image composition
Shilin Lu, Yanzhu Liu, and Adams Wai-Kin Kong · 2023
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Learning controllable degradation for real-world super-resolution via constrained flows
Seobin Park, Dongjin Kim, Sungyong Baik, and Tae Hyun Kim · 2023
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Coser: Bridging image and language for cognitive super-resolution
Haoze Sun, Wenbo Li, Jianzhuang Liu, Haoyu Chen, Renjing Pei, Xueyi Zou, Youliang Yan, and Yujiu Yang · 2023
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Decoupling-and-aggregating for image exposure correction
Yang Wang, Long Peng, Liang Li, Yang Cao, and Zheng-Jun Zha · 2023
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Datasetdm: Synthesizing data with perception annotations using diffusion models
Weijia Wu, Yuzhong Zhao, Hao Chen, Yuchao Gu, Rui Zhao, Yefei He, Hong Zhou, Mike Zheng Shou, and Chunhua Shen · 2023
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Synthesizing realistic image restoration training pairs: A diffusion approach
Tao Yang, Peiran Ren, Lei Zhang, et al · 2023
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Low-res leads the way: Improving generalization for super-resolution by self-supervised learning
Haoyu Chen, Wenbo Li, Jinjin Gu, Jingjing Ren, Haoze Sun, Xueyi Zou, Zhensong Zhang, Youliang Yan, and Lei Zhu · 2024
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Qmambabsr: Burst image super-resolution with query state space model
Xin Di, Long Peng, Peizhe Xia, Wenbo Li, Renjing Pei, Yang Cao, Yang Wang, and Zheng-Jun Zha · 2024
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And: Adversarial neural degradation for learning blind image super-resolution
Fangzhou Luo, Xiaolin Wu, and Yanhui Guo · 2024
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Learning many-to-many mapping for unpaired real-world image super-resolution and downscaling
Wanjie Sun and Zhenzhong Chen · 2024
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Scaling up to excellence: Practicing model scaling for photo-realistic image restoration in the wild
Fanghua Yu, Jinjin Gu, Zheyuan Li, Jinfan Hu, Xiangtao Kong, Xintao Wang, Jingwen He, Yu Qiao, and Chao Dong · 2024
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Resshift: Efficient diffusion model for image super-resolution by residual shifting
Zongsheng Yue, Jianyi Wang, and Chen Change Loy · 2024
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Real-world image super-resolution as multi-task learning
Wenlong Zhang, Xiaohui Li, Guangyuan Shi, Xiangyu Chen, Yu Qiao, Xiaoyun Zhang, Xiao-Ming Wu, and Chao Dong · 2024
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Long Peng, Xin Di, Zhanfeng Feng, Wenbo Li, Renjing Pei, Yang Wang, Xueyang Fu, Yang Cao, and Zheng-Jun Zha · 2025
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