Unsupervised Deraining : Where Asymmetric Contrastive Learning Meets Self-Similarity

Most existing learning-based deraining methods are supervisedly trained on synthetic rainy-clean pairs. The domain gap between the synthetic and real rain makes them less generalized to complex real rainy scenes. Moreover, the existing methods mainly utilize the property of the image or rain layers...

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Publié dans:	IEEE transactions on pattern analysis and machine intelligence. - 1979. - 46(2024), 5 vom: 03. Mai, Seite 2638-2657
Auteur principal:	Chang, Yi (Auteur)
Autres auteurs:	Guo, Yun, Ye, Yuntong, Yu, Changfeng, Zhu, Lin, Zhao, Xile, Yan, Luxin, Tian, Yonghong
Format:	Article en ligne
Langue:	English
Publié:	2024
Accès à la collection:	IEEE transactions on pattern analysis and machine intelligence
Sujets:	Journal Article