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- Bhat, GoutamSwiss Fed Inst Technol, Switzerland (author)
NTIRE 2022 Burst Super-Resolution Challenge
- Article/chapterEnglish2022
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- IEEE,2022
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- LIBRIS-ID:oai:DiVA.org:liu-190497
- https://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-190497URI
- https://doi.org/10.1109/CVPRW56347.2022.00117DOI
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- Language:English
- Summary in:English
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- Funding Agencies|Huawei; Reality Labs; Bending Spoons; MediaTek; OPPO; Oddity; Voyage81; ETH Zurich (Computer Vision Lab); University of Wurzburg (CAIDAS)
- Burst super-resolution has received increased attention in recent years due to its applications in mobile photography. By merging information from multiple shifted images of a scene, burst super-resolution aims to recover details which otherwise cannot be obtained using a simple input image. This paper reviews the NTIRE 2022 challenge on burst super-resolution. In the challenge, the participants were tasked with generating a clean RGB image with 4x higher resolution, given a RAW noisy burst as input. That is, the methods need to perform joint denoising, demosaicking, and super-resolution. The challenge consisted of 2 tracks. Track 1 employed synthetic data, where pixel-accurate high-resolution ground truths are available. Track 2 on the other hand used real-world bursts captured from a handheld camera, along with approximately aligned reference images captured using a DSLR. 14 teams participated in the final testing phase. The top performing methods establish a new state-of-the-art on the burst super-resolution task.
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- Danelljan, MartinSwiss Fed Inst Technol, Switzerland (author)
- Timofte, RaduSwiss Fed Inst Technol, Switzerland; Julius Maximilian Univ Wurzburg, Germany (author)
- Cao, YizhenCommun Univ China, Peoples R China (author)
- Cao, YuntianCommun Univ China, Peoples R China (author)
- Chen, MeiyaXiaomi, Peoples R China (author)
- Chen, XihaoUSTC, Peoples R China; Univ Sci & Technol China, Peoples R China (author)
- Cheng, ShenMegvii Technol, Peoples R China (author)
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- Gang, RuipengUHDTV Res & Applicat Lab, Peoples R China (author)
- Gao, JianSRC B, Peoples R China (author)
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- Huang, LiufengSouth China Univ Technol, Peoples R China (author)
- Jo, YoungsuSogang Univ, South Korea (author)
- Kang, SukjuSogang Univ, South Korea (author)
- Khan, SalmanMBZUAI, U Arab Emirates; Australian Natl Univ ANU, Australia (author)
- Khan, FahadLinköpings universitet,Datorseende,Tekniska fakulteten,MBZUAI, U Arab Emirates(Swepub:liu)fahkh30 (author)
- Kondo, YukiToyota Technol Inst TTI, Japan (author)
- Li, ChenghuaChinese Acad Sci, Peoples R China (author)
- Li, FangyaCommun Univ China, Peoples R China (author)
- Li, JinjingCommun Univ China, Peoples R China (author)
- Li, YouweiMegvii Technol, Peoples R China (author)
- Li, ZechaoNanjing Univ Sci & Technol, Peoples R China (author)
- Liu, ChenmingUHDTV Research and Application Laboratory (author)
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- Wen, ZhihongMegvii Technol, Peoples R China (author)
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- Xiao, ZeyuUSTC, Peoples R China; Univ Sci & Technol China, Peoples R China (author)
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- Yang, JialinWHU, Peoples R China (author)
- Yang, WentaoSouth China Univ Technol, Peoples R China (author)
- Yang, ZhongbaoNanjing Univ Sci & Technol, Peoples R China (author)
- Yasue, FumaToyota Technol Inst TTI, Japan (author)
- Yao, MingdeUSTC, Peoples R China; Univ Sci & Technol China, Peoples R China (author)
- Yu, LeiMegvii Technol, Peoples R China (author)
- Zhang, CongXiaomi, Peoples R China (author)
- Zamir, Syed WaqasIncept Inst Artificial Intelligence IIAI, U Arab Emirates (author)
- Zhang, JianxingSRC B, Peoples R China (author)
- Zhang, ShuohaoHarbin Inst Technol, Peoples R China (author)
- Zhang, ZhiluHarbin Inst Technol, Peoples R China (author)
- Zheng, QianCommun Univ China, Peoples R China (author)
- Zhou, GaofengXiaomi, Peoples R China (author)
- Zhussip, MagauiyaHuawei, Peoples R China (author)
- Zou, XueyiHuawei, Peoples R China (author)
- Zuo, WangmengHarbin Inst Technol, Peoples R China (author)
- Swiss Fed Inst Technol, SwitzerlandSwiss Fed Inst Technol, Switzerland; Julius Maximilian Univ Wurzburg, Germany (creator_code:org_t)
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- In:2022 IEEE/CVF CONFERENCE ON COMPUTER VISION AND PATTERN RECOGNITION WORKSHOPS (CVPRW 2022): IEEE, s. 1040-106097816654873999781665487405
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