| Autor: |
Zhang, Howard, Ba, Yunhao, Yang, Ethan, Upadhyay, Rishi, Wong, Alex, Kadambi, Achuta, Guo, Yun, Xiao, Xueyao, Wang, Xiaoxiong, Li, Yi, Chang, Yi, Yan, Luxin, Zheng, Chaochao, Wang, Luping, Liu, Bin, Khowaja, Sunder Ali, Yoon, Jiseok, Lee, Ik-Hyun, Zhang, Zhao, Wei, Yanyan, Ren, Jiahuan, Zhao, Suiyi, Zheng, Huan |
| Rok vydání: |
2024 |
| Předmět: |
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| Druh dokumentu: |
Working Paper |
| Popis: |
This report reviews the results of the GT-Rain challenge on single image deraining at the UG2+ workshop at CVPR 2023. The aim of this competition is to study the rainy weather phenomenon in real world scenarios, provide a novel real world rainy image dataset, and to spark innovative ideas that will further the development of single image deraining methods on real images. Submissions were trained on the GT-Rain dataset and evaluated on an extension of the dataset consisting of 15 additional scenes. Scenes in GT-Rain are comprised of real rainy image and ground truth image captured moments after the rain had stopped. 275 participants were registered in the challenge and 55 competed in the final testing phase. |
| Databáze: |
arXiv |
| Externí odkaz: |
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