NTIRE 2020 challenge on image demoireing: Methods and results
- Authors
- Yuan, S.; Timofte, R.; Leonardis, A.; Slabaugh, G.; Luo, X.; Zhang, J.; Qu, Y.; Hong, M.; Xie, Y.; Li, C.; Xu, D.; Chu, Y.; Sun, Q.; Liu, S.; Zong, Z.; Nan, N.; Li, C.; Kim, S.; Nam, H.; Kim, J.; Jeong, Jechang; Cheon, M.; Yoon, S.-J.; Kang, B.; Lee, J.; Zheng, B.; Liu, X.; Dai, L.; Chen, J.; Cheng, X.; Fu, Z.; Yang, J.; Lee, C.; Vien, A.G.; Park, H.; Nathan, S.; Beham, M.P.; Mohamed, Mansoor Roomi S.; Lemarchand, F.; Pelcat, M.; Nogues, E.; Puthussery, D.; Hrishikesh, P.S.; Jiji, C.V.; Sinha, A.; Zhao, X.
- Issue Date
- Jun-2020
- Publisher
- IEEE Computer Society
- Citation
- IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops, v.2020-June, pp.1882 - 1893
- Indexed
- SCOPUS
- Journal Title
- IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops
- Volume
- 2020-June
- Start Page
- 1882
- End Page
- 1893
- URI
- https://scholarworks.bwise.kr/hanyang/handle/2021.sw.hanyang/3721
- 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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