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Surv."],"published-print":{"date-parts":[[2024,4,30]]},"abstract":"<jats:p>The rain removal task is to restore a clean image from the contaminated image by separating the background. Since the rise of deep learning in 2016, the task of image deraining has also stepped into the era of deep learning. Numerous researchers have devoted themselves to the field of computer vision and pattern recognition. However, there is still a lack of comprehensive review papers focused on using deep learning to perform rain removal tasks. In this paper, we present a comprehensive review of single image deraining based on deep learning over the past ten years. Two categories of deraining methods are discussed: the data-driven approach and the data-model-based approach. For the first type, we compare the existing network structures and loss functions. For the second type, we analyze the combination of different deraining models with deep learning, and each branch method is introduced in detail. Additionally, we quantitatively investigate the performances of the existing state-of-the-art methods on both publicly synthetic and real datasets. The trend of image deraining is also discussed.<\/jats:p>\n          <jats:p\/>","DOI":"10.1145\/3625818","type":"journal-article","created":{"date-parts":[[2023,10,2]],"date-time":"2023-10-02T08:24:48Z","timestamp":1696235088000},"page":"1-35","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":14,"title":["A Survey of Single Image Rain Removal Based on Deep Learning"],"prefix":"10.1145","volume":"56","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-0995-7469","authenticated-orcid":false,"given":"Zhipeng","family":"Su","sequence":"first","affiliation":[{"name":"School of Informatics Xiamen University, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0879-3298","authenticated-orcid":false,"given":"Yixiong","family":"Zhang","sequence":"additional","affiliation":[{"name":"School of Electronic Science and Engineering (National Model Microelectronics College), Xiamen University, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0009-0003-0200-4320","authenticated-orcid":false,"given":"Jianghong","family":"Shi","sequence":"additional","affiliation":[{"name":"School of Informatics Xiamen University, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-5241-0069","authenticated-orcid":false,"given":"Xiao-Ping","family":"Zhang","sequence":"additional","affiliation":[{"name":"Tsinghua Shenzhen International Graduate School, Shenzhen 518055, China, and also with the Department of Electrical, Computer, and Biomedical Engineering, Toronto MetropolitanUniversity"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"320","published-online":{"date-parts":[[2023,11,10]]},"reference":[{"key":"e_1_3_1_2_2","doi-asserted-by":"publisher","DOI":"10.1109\/ICIP.2019.8803308"},{"key":"e_1_3_1_3_2","doi-asserted-by":"publisher","DOI":"10.1109\/TIE.2017.2682036"},{"key":"e_1_3_1_4_2","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR46437.2021.00765"},{"key":"e_1_3_1_5_2","doi-asserted-by":"publisher","DOI":"10.1109\/WACV.2019.00151"},{"key":"e_1_3_1_6_2","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR46437.2021.01212"},{"key":"e_1_3_1_7_2","doi-asserted-by":"publisher","DOI":"10.1109\/CVPRW53098.2021.00027"},{"key":"e_1_3_1_8_2","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR52688.2022.00206"},{"key":"e_1_3_1_9_2","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2019.00020"},{"key":"e_1_3_1_10_2","doi-asserted-by":"publisher","DOI":"10.24963\/ijcai.2021\/90"},{"key":"e_1_3_1_11_2","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR42600.2020.01457"},{"key":"e_1_3_1_12_2","doi-asserted-by":"publisher","DOI":"10.1109\/TCSVT.2021.3063853"},{"key":"e_1_3_1_13_2","volume-title":"International Conference on Machine Learning","author":"Dosovitskiy Alexey","year":"2021","unstructured":"Alexey Dosovitskiy, Lucas Beyer, Alexander Kolesnikov, Dirk Weissenborn, Xiaohua Zhai, Thomas Unterthiner, Mostafa Dehghani, Matthias Minderer, Georg Heigold, Sylvain Gelly, Jakob Uszkoreit, and Neil Houlsby. 2021. 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