no code implementations • 15 Aug 2023 • Zhentao Fan, Hongming Chen, Yufeng Li
Recently, Transformer-based architecture has been introduced into single image deraining task due to its advantage in modeling non-local information.
no code implementations • 15 Mar 2022 • Xiang Chen, Zhentao Fan, Pengpeng Li, Longgang Dai, Caihua Kong, Zhuoran Zheng, Yufeng Huang, Yufeng Li
Then these negative adversaries are trained end-to-end together with the backbone representation network to enhance the discriminative information and promote factor disentanglement performance by maximizing the adversarial contrastive loss.
no code implementations • CVPR 2022 • Xiang Chen, Jinshan Pan, Kui Jiang, Yufeng Li, Yufeng Huang, Caihua Kong, Longgang Dai, Zhentao Fan
Learning single image deraining (SID) networks from an unpaired set of clean and rainy images is practical and valuable as acquiring paired real-world data is almost infeasible.