NTIRE 2021 Challenge on Burst Super-Resolution: Methods and Results

This paper reviews the NTIRE2021 challenge on burst super-resolution. Given a RAW noisy burst as input, the task in the challenge was to generate a clean RGB image with 4 times higher resolution. The challenge contained two tracks; Track 1 evaluating on synthetically generated data, and Track 2 usin...

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Published in2021 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW) pp. 613 - 626
Main Authors Bhat, Goutam, Danelljan, Martin, Timofte, Radu, Akita, Kazutoshi, Cho, Wooyeong, Fan, Haoqiang, Jia, Lanpeng, Kim, Daeshik, Lecouat, Bruno, Li, Youwei, Liu, Shuaicheng, Liu, Ziluan, Luo, Ziwei, Maeda, Takahiro, Mairal, Julien, Micheloni, Christian, Mo, Xuan, Oba, Takeru, Ostyakov, Pavel, Ponce, Jean, Son, Sanghyeok, Sun, Jian, Ukita, Norimichi, Muhammad, Rao, Yan, Umer Youliang, Yu, Lei, Zhussip, Magauiya, Zou, Xueyi
Format Conference Proceeding
LanguageEnglish
Published IEEE 01.06.2021
Subjects
Cameras
Computer vision
Conferences
Merging
Noise measurement
Pattern recognition
Superresolution
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Summary:This paper reviews the NTIRE2021 challenge on burst super-resolution. Given a RAW noisy burst as input, the task in the challenge was to generate a clean RGB image with 4 times higher resolution. The challenge contained two tracks; Track 1 evaluating on synthetically generated data, and Track 2 using real-world bursts from mobile camera. In the final testing phase, 6 teams submitted results using a diverse set of solutions. The top-performing methods set a new state-of-the-art for the burst super-resolution task.
ISSN:2160-7516
DOI:10.1109/CVPRW53098.2021.00073