AIM 2020 challenge on video extreme super-resolution: methods and results

• Main Authors: FUOLI, D., HUANG, Zhiwu, GU, S., TIMOFTE, R., RAVENTOS, A., ESFANDIARI, A., KAROUT, S., XU, X., LI, X., XIONG, X., WANG, J., NAVARRETE, Michelini P., ZHANG, W., ZHANG, D., ZHU, H., XIA, D., CHEN, H., GU, J., ZHANG, Z., ZHAO, T.
• Format: text
• Language: English
• Published: Institutional Knowledge at Singapore Management University 2020
• Subjects: Challenge; Extreme super-resolution; Video enhancement; Video restoration; Databases and Information Systems
• Online Access: https://ink.library.smu.edu.sg/sis_research/6549; https://ink.library.smu.edu.sg/context/sis_research/article/7552/viewcontent/AIM_2020_Challenge_on_Video_Extreme_Super_Resoluti.pdf
• Institution: Singapore Management University

This paper reviews the video extreme super-resolution challenge associated with the AIM 2020 workshop at ECCV 2020. Common scaling factors for learned video super-resolution (VSR) do not go beyond factor 4. Missing information can be restored well in this region, especially in HR videos, where the h...