Deep Video Super-Resolution Network Using Dynamic Upsampling Filters Without Explicit Motion Compensation. - Younghyun Jo; Seoung Wug Oh; Jaeyeon Kang; Seon Joo Kim (CVPR, 2018)

Investigating Loss Functions for Extreme Super-Resolution. - Younghyun Jo; Sejong Yang; Seon Joo Kim (CVPR Workshops, 2020)

NTIRE 2020 Challenge on Perceptual Extreme Super-Resolution: Methods and Results. - Kai Zhang 008; Shuhang Gu; Radu Timofte; Taizhang Shang; Qiuju Dai; Shengchen Zhu; Tong Yang; Yandong Guo; Younghyun Jo; Sejong Yang; Seon Joo Kim; Lin Zha; et al. (CVPR Workshops, 2020)

Deep Space-Time Video Upsampling Networks. - Jaeyeon Kang; Younghyun Jo; Seoung Wug Oh; Peter Vajda; Seon Joo Kim (ECCV (10), 2020)

Learning the Loss Functions in a Discriminative Space for Video Restoration. - Younghyun Jo; Jaeyeon Kang; Seoung Wug Oh; Seonghyeon Nam; Peter Vajda; Seon Joo Kim (CoRR, 2020)

Practical Single-Image Super-Resolution Using Look-Up Table. - Younghyun Jo; Seon Joo Kim (CVPR, 2021)

Tackling the Ill-Posedness of Super-Resolution Through Adaptive Target Generation. - Younghyun Jo; Seoung Wug Oh; Peter Vajda; Seon Joo Kim (CVPR, 2021)

SRFlow-DA: Super-Resolution Using Normalizing Flow With Deep Convolutional Block. - Younghyun Jo; Sejong Yang; Seon Joo Kim (CVPR Workshops, 2021)

ATTIQA: Generalizable Image Quality Feature Extractor Using Attribute-Aware Pretraining. - Daekyu Kwon; Dongyoung Kim; Sehwan Ki; Younghyun Jo; Hyong-Euk Lee; Seon Joo Kim (ACCV (4), 2022)

Accelerating Image Super-Resolution Networks with Pixel-Level Classification. - Jinho Jeong 003; Jinwoo Kim; Younghyun Jo; Seon Joo Kim (ECCV (3), 2024)

A Preliminary Study of the Mobile Robot-Based Cooperative System for Outdoor Hazardous Testing Spaces. - Boseong Kim; Yoonkeon Kim; Eungsoo Kim; Jaeun Kang; Kihoon Kim; Younghyun Jo (UR, 2024)

CLIP-Guided Attribute Aware Pretraining for Generalizable Image Quality Assessment. - Daekyu Kwon; Dongyoung Kim; Sehwan Ki; Younghyun Jo; Hyong-Euk Lee; Seon Joo Kim (CoRR, 2024)