GT-Rain Single Image Deraining Challenge Report
Fuente:
arXiv
Saved in:
| Main Authors: | , , , , , , , , , , , , , , , , , , , , , , |
|---|---|
| Format: | Preprint |
| Published: |
2024
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1866914719589203968 |
|---|---|
| author | 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 |
| author_facet | 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 |
| contents | 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. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2403_12327 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | GT-Rain Single Image Deraining Challenge Report 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 Computer Vision and Pattern Recognition Machine Learning 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. |
| title | GT-Rain Single Image Deraining Challenge Report |
| topic | Computer Vision and Pattern Recognition Machine Learning |
| url | https://arxiv.org/abs/2403.12327 |