NTIRE 2020 Challenge on Image Demoireing: Methods and Results
- Authors
- Yuan, Shanxin; Timofte, Radu; Leonardis, Ales; Slabaugh, Gregory; Luo, Xiaotong; Zhang, Jiangtao; Qu, Yanyun; Hong, Ming; Xie, Yuan; Li, Cuihua; Xu, Dejia; Chu, Yihao; Sun, Qingyan; Liu, Shuai; Zong, Ziyao; Nan, Nan; Li, Chenghua; Kim, Sangmin; Nam, Hyungjoon; Kim, Jisu; Jeong, Jechang; Cheon, Manri; Yoon, Sung-Jun; Kang, Byungyeon; Lee, Junwoo; Zheng, Bolun; Liu, Xiaohong; Dai, Linhui; Chen, Jun; Cheng, Xi; Fu, Zhenyong; Yang, Jian; Lee, Chul; Vien, An Gia; Park, Hyunkook; Nathan, Sabari; Beham, M. Parisa; Roomi, S. Mohamed Mansoor; Lemarchand, Florian; Pelcat, Maxime; Nogues, Erwan; Puthussery, Densen; Hrishikesh, P. S.; Jiji, C., V; Sinha, Ashish; Zhao, Xuan
- Issue Date
- Jun-2020
- Publisher
- IEEE COMPUTER SOC
- Citation
- 2020 IEEE/CVF CONFERENCE ON COMPUTER VISION AND PATTERN RECOGNITION WORKSHOPS (CVPRW 2020), v.2020-June, pp 1882 - 1893
- Pages
- 12
- Indexed
- SCOPUS
- Journal Title
- 2020 IEEE/CVF CONFERENCE ON COMPUTER VISION AND PATTERN RECOGNITION WORKSHOPS (CVPRW 2020)
- Volume
- 2020-June
- Start Page
- 1882
- End Page
- 1893
- URI
- https://scholarworks.dongguk.edu/handle/sw.dongguk/7174
- DOI
- 10.1109/CVPRW50498.2020.00238
- ISSN
- 2160-7508
- Abstract
- This paper reviews the Challenge on Image Demoireing that was part of the New Trends in Image Restoration and Enhancement (NTIRE) workshop, held in conjunction with CVPR 2020. Demoireing is a difficult task of removing moire patterns from an image to reveal an underlying clean image. The challenge was divided into two tracks. Track 1 targeted the single image demoireing problem, which seeks to remove moire patterns from a single image. Track 2 focused on the burst demoireing problem, where a set of degraded moire images of the same scene were provided as input, with the goal of producing a single demoired image as output. The methods were ranked in terms of their fidelity, measured using the peak signal-to-noise ratio (PSNR) between the ground truth clean images and the restored images produced by the participants' methods. The tracks had 142 and 99 registered participants, respectively, with a total of 14 and 6 submissions in the final testing stage. The entries span the current state-of-the-art in image and burst image demoireing problems.
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Collections - College of Advanced Convergence Engineering > Department of Computer Science and Artificial Intelligence > 1. Journal Articles

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