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In IEEE\/CVF Conference on Computer Vision and Pattern Recognition (CVPR). Cheng Ma, Yongming Rao, Yean Cheng, Ce Chen, Jiwen Lu, and J. Zhou. 2020. Structure-Preserving Super Resolution With Gradient Guidance. In IEEE\/CVF Conference on Computer Vision and Pattern Recognition (CVPR)."},{"key":"e_1_3_2_2_35_1","volume-title":"Efficient Super Resolution Using Binarized Neural Network. IEEE\/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW)","author":"Ma Y.","year":"2019","unstructured":"Y. Ma , Hongyu Xiong , Zhe Hu , and L. Ma . 2019 . Efficient Super Resolution Using Binarized Neural Network. IEEE\/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW) ( 2019 ). Y. Ma, Hongyu Xiong, Zhe Hu, and L. Ma. 2019. Efficient Super Resolution Using Binarized Neural Network. IEEE\/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW) (2019)."},{"key":"e_1_3_2_2_36_1","doi-asserted-by":"crossref","unstructured":"Hongzi Mao R. Netravali and M. Alizadeh. 2017. Neural Adaptive Video Streaming with Pensieve. SIGCOMM (2017).  Hongzi Mao R. Netravali and M. Alizadeh. 2017. Neural Adaptive Video Streaming with Pensieve. SIGCOMM (2017).","DOI":"10.1145\/3098822.3098843"},{"key":"e_1_3_2_2_37_1","volume-title":"Bovik","author":"Mittal Anish","year":"2013","unstructured":"Anish Mittal , Rajiv Soundararajan , and Alan C . Bovik . 2013 . Making a \"Completely Blind\" Image Quality Analyzer. IEEE Signal Processing Letters ( 2013). Anish Mittal, Rajiv Soundararajan, and Alan C. Bovik. 2013. Making a \"Completely Blind\" Image Quality Analyzer. IEEE Signal Processing Letters (2013)."},{"key":"e_1_3_2_2_38_1","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-58583-9_45"},{"key":"e_1_3_2_2_39_1","first-page":"1","article-title":"Nonlinear Total Variation Based Noise Removal","volume":"60","author":"Rudin Leonid I.","year":"1992","unstructured":"Leonid I. Rudin , Stanley Osher , and Emad Fatemi . 1992 . Nonlinear Total Variation Based Noise Removal Algorithms. Phys. D 60 , 1 - 4 (Nov. 1992), 259--268. Leonid I. Rudin, Stanley Osher, and Emad Fatemi. 1992. Nonlinear Total Variation Based Noise Removal Algorithms. Phys. D 60, 1-4 (Nov. 1992), 259--268.","journal-title":"Algorithms. Phys. D"},{"key":"e_1_3_2_2_40_1","volume-title":"IEEE\/CVF Conference on Computer Vision and Pattern Recognition (CVPR).","author":"Shocher Assaf","unstructured":"Assaf Shocher , N. Cohen , and M. Irani . 2018. \"Zero-Shot\" Super-Resolution Using Deep Internal Learning . In IEEE\/CVF Conference on Computer Vision and Pattern Recognition (CVPR). Assaf Shocher, N. Cohen, and M. Irani. 2018. \"Zero-Shot\" Super-Resolution Using Deep Internal Learning. In IEEE\/CVF Conference on Computer Vision and Pattern Recognition (CVPR)."},{"key":"e_1_3_2_2_41_1","volume-title":"Meta-Transfer Learning for Zero-Shot Super-Resolution. IEEE\/CVF Conference on Computer Vision and Pattern Recognition (CVPR).","author":"Soh Jae Woong","unstructured":"Jae Woong Soh , Sunwoo Cho , and N. I. Cho . 2020 . Meta-Transfer Learning for Zero-Shot Super-Resolution. IEEE\/CVF Conference on Computer Vision and Pattern Recognition (CVPR). Jae Woong Soh, Sunwoo Cho, and N. I. Cho. 2020. Meta-Transfer Learning for Zero-Shot Super-Resolution. IEEE\/CVF Conference on Computer Vision and Pattern Recognition (CVPR)."},{"key":"e_1_3_2_2_42_1","volume-title":"Natural and Realistic Single Image Super-Resolution With Explicit Natural Manifold Discrimination. In IEEE\/CVF Conference on Computer Vision and Pattern Recognition (CVPR).","author":"Soh Jae Woong","unstructured":"Jae Woong Soh , G. Y. Park , Junho Jo , and N. I. Cho . 2019 . Natural and Realistic Single Image Super-Resolution With Explicit Natural Manifold Discrimination. In IEEE\/CVF Conference on Computer Vision and Pattern Recognition (CVPR). Jae Woong Soh, G. Y. 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In European Conference on Computer Vision Workshops (ECCVW). Xintao Wang, Ke Yu, Shixiang Wu, Jinjin Gu, Yihao Liu, Chao Dong, Chen Change Loy, Yu Qiao, and Xiaoou Tang. 2018. ESRGAN: Enhanced Super-Resolution Generative Adversarial Networks. In European Conference on Computer Vision Workshops (ECCVW)."},{"key":"e_1_3_2_2_46_1","unstructured":"Yiding Wang Weiyan Wang Junxue Zhang J. Jiang and K. Chen. 2019. Bridging the Edge-Cloud Barrier for Real-time Advanced Vision Analytics. In HotCloud.  Yiding Wang Weiyan Wang Junxue Zhang J. Jiang and K. Chen. 2019. Bridging the Edge-Cloud Barrier for Real-time Advanced Vision Analytics. In HotCloud."},{"key":"e_1_3_2_2_47_1","volume-title":"Simoncelli","author":"Wang Zhou","year":"2004","unstructured":"Zhou Wang , Alan C. Bovik , Hamid R. Sheikh , and Eero P . Simoncelli . 2004 . Image quality assessment: from error visibility to structural similarity. IEEE Transactions on Image Processing (TIP) ( 2004). Zhou Wang, Alan C. Bovik, Hamid R. 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