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Investigating Loss Functions for Extreme Super-Resolution., , and . CVPR Workshops, page 1705-1712. Computer Vision Foundation / IEEE, (2020)Practical Single-Image Super-Resolution Using Look-Up Table., and . CVPR, page 691-700. Computer Vision Foundation / IEEE, (2021)Learning the Loss Functions in a Discriminative Space for Video Restoration., , , , , and . CoRR, (2020)Deep Space-Time Video Upsampling Networks., , , , and . ECCV (10), volume 12355 of Lecture Notes in Computer Science, page 701-717. Springer, (2020)SRFlow-DA: Super-Resolution Using Normalizing Flow With Deep Convolutional Block., , and . CVPR Workshops, page 364-372. Computer Vision Foundation / IEEE, (2021)Tackling the Ill-Posedness of Super-Resolution Through Adaptive Target Generation., , , and . CVPR, page 16236-16245. Computer Vision Foundation / IEEE, (2021)NTIRE 2020 Challenge on Perceptual Extreme Super-Resolution: Methods and Results., , , , , , , , , and 53 other author(s). CVPR Workshops, page 2045-2057. Computer Vision Foundation / IEEE, (2020)