학술논문

NTIRE 2021 Challenge on Video Super-Resolution
Document Type
Conference
Author
Son, SanghyunLee, SuyoungNah, SeungjunTimofte, RaduLee, Kyoung MuChan, Kelvin C. K.Zhou, ShangchenXu, XiangyuLoy, Chen ChangeJiang, BoyuanLin, ChumingDong, YuchunLuo, DonghaoChu, WenqingJi, XiaozhongYang, SiqianTai, YingWang, ChengjieLi, JilinHuang, FeiyueChen, ChengpengChu, XiaojieZhang, JieLu, XinChen, LiangyuLin, JingDu, GuodongHao, JiaZou, XueyiZhang, QiJiang, LielinLi, XinZheng, HeLiu, FanglongHe, DongliangLi, FuDang, QingqingYi, PengWang, ZhongyuanJiang, KuiJiang, JunjunMa, JiayiChen, YuxiangWang, YutongLiu, TingSun, QichaoLiang, HuanweiLi, YimingLi, ZekunRuan, ZhuboShang, FanjieGuo, ChenLi, HainingLuo, RenjunShen, LongjieZafirouli, KassianiKarageorgos, KonstantinosKonstantoudakis, KonstantinosDimou, AnastasiosDaras, PetrosSong, XiaoweiZhuo, XuLiu, HanxiGuo, MengxiLi, JunlinLi, YuZhu, YeWang, QingZhao, ShijieSun, XiaopengZhan, GenXie, TangxinJia, YuLu, YunhuaZhang, WenhaoSun, MengdiMichelini, Pablo NavarreteZhang, XuehengJiang, HaoChen, ZhiyuChen, LiXiong, ZhiweiXiao, ZeyuXu, RuikangCheng, ZhenFu, XueyangSong, FenglongLuo, ZhipengYao, YuehanDutta, SaikatShah, Nisarg A.Dipta Das, SouryaZhao, PengShi, YukaiLiu, HongyingShang, FanhuaLiu, YuanyuanChen, FeiYu, FangxuGao, RuishengBai, YixinHeo, JeonghwanYue, ShijieLi, ChenghuaLi, JinjingZheng, QianGang, RuipengSong, RuixiaWee, SeungwooJeong, JechangLi, ChenWen, GeyingjieChai, XinningSong, Li
Source
2021 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW) CVPRW Computer Vision and Pattern Recognition Workshops (CVPRW), 2021 IEEE/CVF Conference on. :166-181 Jun, 2021
Subject
Computing and Processing
Computer vision
Casting
Conferences
Superresolution
Focusing
Pattern recognition
Image restoration
Language
ISSN
2160-7516
Abstract
Super-Resolution (SR) is a fundamental computer vision task that aims to obtain a high-resolution clean image from the given low-resolution counterpart. This paper reviews the NTIRE 2021 Challenge on Video Super-Resolution. We present evaluation results from two competition tracks as well as the proposed solutions. Track 1 aims to develop conventional video SR methods focusing on the restoration quality. Track 2 assumes a more challenging environment with lower frame rates, casting spatio-temporal SR problem. In each competition, 247 and 223 participants have registered, respectively. During the final testing phase, 14 teams competed in each track to achieve state-of-the-art performance on video SR tasks.