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Degradation-Guided cross-consistent deep unfolding network for video restoration under diverse weathers.

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第一作者： Yuanshuo,Cheng

第一单位： Qingdao Institute of Software, School of computer science and technology, China University of Petroleum (East China), QingDao, 266580, China. Electronic address: cys1294414023@gmail.com.

作者： Yuanshuo,Cheng ^[1] ; Mingwen,Shao ^[2] ; Yecong,Wan ^[3] ; Yuanjian,Qiao ^[4] ; Wangmeng,Zuo ^[5] ; Deyu,Meng ^[6]

作者单位： Qingdao Institute of Software, School of computer science and technology, China University of Petroleum (East China), QingDao, 266580, China. Electronic address: cys1294414023@gmail.com. ^[1] Artificial Intelligence Research Institute, Shenzhen University of Advanced Technology, Shenzhen, 518107, China. Electronic address: smw278@126.com. ^[2] Qingdao Institute of Software, School of computer science and technology, China University of Petroleum (East China), QingDao, 266580, China. Electronic address: yecongwan@gmail.com. ^[3] Qingdao Institute of Software, School of computer science and technology, China University of Petroleum (East China), QingDao, 266580, China. Electronic address: yjqiao@s.upc.edu.cn. ^[4] School of Computer Science and Technology, Harbin Institute of Technology, Harbin, 150001, China. Electronic address: cswmzuo@gmail.com. ^[5] Institute for Information and System Sciences, Xi'an Jiaotong University, Xi'an, 710049, China. Electronic address: dymeng@mail.xjtu.edu.cn. ^[6]

关键词 Deep unfolding network Degradation-adaptive model Diverse adverse weathers Video restoration

医学主题词录像(Video Recording);算法(Algorithms);人类(Humans);图像处理, 计算机辅助(Image Processing, Computer-Assisted)

DOI 10.1016/j.neunet.2025.107700

PMID 40578215

发布时间 2025-09-06

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