NTIRE 2025 Challenge on Day and Night Raindrop Removal for Dual-Focused Images: Methods and Results
Xin Li, Yeying Jin, Xin Jin, Zongwei Wu, Bingchen Li, Yufei Wang, Wenhan Yang, Yu Li, Zhibo Chen, Bihan Wen, Robby T. Tan, Radu Timofte, Qiyu Rong, Hongyuan Jing, Mengmeng Zhang, Jinglong Li, Xiangyu Lu, Yi Ren, Yuting Liu, Meng Zhang, Xiang Chen, Qiyuan Guan, Jiangxin Dong, Jinshan Pan, Conglin Gou, Qirui Yang, Fangpu Zhang, Yunlong Lin, Sixiang Chen, Guoxi Huang, Ruirui Lin, Yan Zhang, Jingyu Yang, Huanjing Yue, Jiyuan Chen, Qiaosi Yi, Hongjun Wang, Chenxi Xie, Shuai Li, Yuhui Wu, Kaiyi Ma, Jiakui Hu, Juncheng Li, Liwen Pan, Guangwei Gao, Wenjie Li, Zhenyu Jin, Heng Guo, Zhanyu Ma, Yubo Wang, Jinghua Wang, Wangzhi Xing, Anjusree Karnavar, Diqi Chen, Mohammad Aminul Islam, Hao Yang, Ruikun Zhang, Liyuan Pan, Qianhao Luo, XinCao, Han Zhou, Yan Min, Wei Dong, Jun Chen, Taoyi Wu, Weijia Dou, Yu Wang, Shengjie Zhao, Yongcheng Huang, Xingyu Han, Anyan Huang, Hongtao Wu, Hong Wang, Yefeng Zheng, Abhijeet Kumar, Aman Kumar, Marcos V. Conde, Paula Garrido, Daniel Feijoo, Juan C. Benito, Guanglu Dong, Xin Lin, Siyuan Liu, Tianheng Zheng, Jiayu Zhong, Shouyi Wang, Xiangtai Li, Lanqing Guo, Lu Qi, Chao Ren, Shuaibo Wang, Shilong Zhang, Wanyu Zhou, Yunze Wu, Qinzhong Tan, Jieyuan Pei, Zhuoxuan Li, Jiayu Wang, Haoyu Bian, Haoran Sun, Subhajit Paul, Ni Tang, Junhao Huang, Zihan Cheng, Hongyun Zhu, Yuehan Wu, Kaixin Deng, Hang Ouyang, Tianxin Xiao, Fan Yang, Zhizun Luo, Zeyu Xiao, Zhuoyuan Li, Nguyen Pham Hoang Le, An Dinh Thien, Son T. Luu, Kiet Van Nguyen, Ronghua Xu, Xianmin Tian, Weijian Zhou, Jiacheng Zhang, Yuqian Chen, Yihang Duan, Yujie Wu, Suresh Raikwar, Arsh Garg, Kritika, Jianhua Zheng, Xiaoshan Ma, Ruolin Zhao, Yongyu Yang, Yongsheng Liang, Guiming Huang, Qiang Li, Hongbin Zhang, Xiangyu Zheng, A. N. Rajagopalan
TL;DR
The paper presents the NTIRE 2025 Challenge on Day and Night Raindrop Removal for Dual-Focused Images and the Raindrop Clarity dataset, addressing real-world raindrop degradation under diverse lighting and focus. It establishes a standardized evaluation protocol using PSNR, SSIM, and LPIPS and reports robust challenge results across 29 teams, highlighting a range of approaches from transformer- and diffusion-based methods to multi-stage and test-time adaptation strategies. The top methods demonstrate strong performance with varied efficiency profiles, underscoring the feasibility of high-quality raindrop removal in both daytime and nighttime conditions and the potential for cross-domain generalization. Overall, the challenge provides a comprehensive benchmark and a rich set of techniques that advance practical deraining for dual-focused imaging in real-world scenarios.
Abstract
This paper reviews the NTIRE 2025 Challenge on Day and Night Raindrop Removal for Dual-Focused Images. This challenge received a wide range of impressive solutions, which are developed and evaluated using our collected real-world Raindrop Clarity dataset. Unlike existing deraining datasets, our Raindrop Clarity dataset is more diverse and challenging in degradation types and contents, which includes day raindrop-focused, day background-focused, night raindrop-focused, and night background-focused degradations. This dataset is divided into three subsets for competition: 14,139 images for training, 240 images for validation, and 731 images for testing. The primary objective of this challenge is to establish a new and powerful benchmark for the task of removing raindrops under varying lighting and focus conditions. There are a total of 361 participants in the competition, and 32 teams submitting valid solutions and fact sheets for the final testing phase. These submissions achieved state-of-the-art (SOTA) performance on the Raindrop Clarity dataset. The project can be found at https://lixinustc.github.io/CVPR-NTIRE2025-RainDrop-Competition.github.io/.