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In IEEE Conference on Computer Vision and Pattern Recognition Workshop. 114--125","author":"Timofte Radu","year":"2017","unstructured":"Radu Timofte, Eirikur Agustsson, Luc Van Gool, Ming-Hsuan Yang, and Lei Zhang. 2017. NTIRE 2017 Challenge on Single Image Super-resolution: Methods and Results. In IEEE Conference on Computer Vision and Pattern Recognition Workshop. 114--125."},{"key":"e_1_3_2_1_61_1","volume-title":"Conference and Workshop on Neural Information Processing Systems 30","author":"Vaswani Ashish","year":"2017","unstructured":"Ashish Vaswani, Noam Shazeer, Niki Parmar, Jakob Uszkoreit, Llion Jones, Aidan N Gomez, Lukasz Kaiser, and Illia Polosukhin. 2017. Attention is All You Need. Conference and Workshop on Neural Information Processing Systems 30 (2017)."},{"key":"e_1_3_2_1_62_1","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v37i2.25353"},{"key":"e_1_3_2_1_63_1","volume-title":"Kelvin CK Chan, and Chen Change Loy","author":"Wang Jianyi","year":"2023","unstructured":"Jianyi Wang, Zongsheng Yue, Shangchen Zhou, Kelvin CK Chan, and Chen Change Loy. 2023. Exploiting Diffusion Prior for Real-World Image Super-Resolution. arXiv preprint arXiv:2305.07015 (2023)."},{"key":"e_1_3_2_1_64_1","volume-title":"Unsupervised Degradation Representation Learning for Blind Super-resolution. In IEEE Conference on Computer Vision and Pattern Recognition. 10581--10590","author":"Wang Longguang","year":"2021","unstructured":"Longguang Wang, Yingqian Wang, Xiaoyu Dong, Qingyu Xu, Jungang Yang, Wei An, and Yulan Guo. 2021. Unsupervised Degradation Representation Learning for Blind Super-resolution. In IEEE Conference on Computer Vision and Pattern Recognition. 10581--10590."},{"key":"e_1_3_2_1_65_1","volume-title":"Real-ESRGAN: Training Real-world Blind Super-resolution with Pure Synthetic Data. In Proc. IEEE.","author":"Wang Xintao","unstructured":"Xintao Wang, Liangbin Xie, Chao Dong, and Ying Shan. [n. d.]. Real-ESRGAN: Training Real-world Blind Super-resolution with Pure Synthetic Data. In Proc. IEEE."},{"key":"e_1_3_2_1_66_1","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2018.00070"},{"key":"e_1_3_2_1_67_1","volume-title":"ESRGAN: Enhanced Super-resolution Generative Adversarial Networks. In European Conference on Computer Vision Workshop. 0--0.","author":"Wang Xintao","year":"2018","unstructured":"Xintao Wang, Ke Yu, Shixiang Wu, Jinjin Gu, Yihao Liu, Chao Dong, Yu Qiao, and Chen Change Loy. 2018. ESRGAN: Enhanced Super-resolution Generative Adversarial Networks. 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Springer, 101--117."},{"key":"e_1_3_2_1_71_1","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR46437.2021.01318"},{"key":"e_1_3_2_1_72_1","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV51070.2023.01204"},{"key":"e_1_3_2_1_73_1","volume-title":"Proceedings of the International Conference on Machine Learning","author":"Xie Liangbin","year":"2023","unstructured":"Liangbin Xie, Xintao Wang, Xiangyu Chen, Gen Li, Ying Shan, Jiantao Zhou, and Chao Dong. 2023. DeSRA: Detect and Delete the Artifacts of GAN-based Real-World Super-Resolution Models. Proceedings of the International Conference on Machine Learning (2023)."},{"key":"e_1_3_2_1_74_1","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR52729.2023.00881"},{"key":"e_1_3_2_1_75_1","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR52688.2022.00558"},{"key":"e_1_3_2_1_76_1","volume-title":"Pixel-Aware Stable Diffusion for Realistic Image Super-resolution and Personalized Stylization. arXiv preprint arXiv:2308.14469","author":"Yang Tao","year":"2023","unstructured":"Tao Yang, Peiran Ren, Xuansong Xie, and Lei Zhang. 2023. Pixel-Aware Stable Diffusion for Realistic Image Super-resolution and Personalized Stylization. arXiv preprint arXiv:2308.14469 (2023)."},{"key":"e_1_3_2_1_77_1","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV51070.2023.01198"},{"key":"e_1_3_2_1_78_1","doi-asserted-by":"publisher","DOI":"10.1109\/WACV56688.2023.00493"},{"key":"e_1_3_2_1_79_1","volume-title":"Proceedings of the Advances in Neural Information Processing Systems","author":"Yue Zongsheng","year":"2023","unstructured":"Zongsheng Yue, Jianyi Wang, and Chen Change Loy. 2023. Resshift: Efficient diffusion model for image super-resolution by residual shifting. Proceedings of the Advances in Neural Information Processing Systems (2023)."},{"key":"e_1_3_2_1_80_1","volume-title":"Blind Image Super-resolution with Elaborate Degradation Modeling on Noise and Kernel. 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