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

Goutam Bhat, Martin Danelljan, Radu Timofte, Kazutoshi Akita, Wooyeong Cho, Haoqiang Fan, Lanpeng Jia, Dae‐Shik Kim, Bruno Lecouat, Youwei Li, Shuaicheng Liu, Ziluan Liu, Ziwei Luo, Takahiro Maeda, Julien Mairal, Christian Micheloni, Xuan Mo, Takeru Oba, Pavel Ostyakov, Jean Ponce, Sanghyeok Son, Jian Sun, Norimichi Ukita, Rao Muhammad, Umer Youliang Yan, Lei Yu, Magauiya Zhussip, Xueyi Zou

202133 citationsDOI

Abstract

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.

Topics & Concepts

Computer scienceArtificial intelligenceTask (project management)Resolution (logic)Track (disk drive)Set (abstract data type)Computer visionImage resolutionRGB color modelData setImage (mathematics)Pattern recognition (psychology)EngineeringSystems engineeringOperating systemProgramming languageAdvanced Image Processing TechniquesImage Processing Techniques and ApplicationsAdvanced Vision and Imaging
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