标题:Gated context aggregation network for image dehazing and deraining
作者:Chen, Dongdong ;He, Mingming ;Fan, Qingnan ;Liao, Jing ;Zhang, Liheng ;Hou, Dongdong ;Yuan, Lu ;Hua, Gang
作者机构:[Chen, Dongdong ;Hou, Dongdong ] University of Science and Technology of China, China;[Fan, Qingnan ] Shandong University, China;[He, Mingming ] Hong 更多
会议名称:19th IEEE Winter Conference on Applications of Computer Vision, WACV 2019
会议日期:7 January 2019 through 11 January 2019
来源:Proceedings - 2019 IEEE Winter Conference on Applications of Computer Vision, WACV 2019
出版年:2019
页码:1375-1383
DOI:10.1109/WACV.2019.00151
摘要:Image dehazing aims to recover the uncorrupted content from a hazy image. Instead of leveraging traditional low-level or handcrafted image priors as the restoration constraints, e.g., dark channels and increased contrast, we propose an end-to-end gated context aggregation network to directly restore the final haze-free image. In this network, we adopt the latest smoothed dilation technique to help remove the gridding artifacts caused by the widely-used dilated convolution with negligible extra parameters, and leverage a gated sub-network to fuse the features from different levels. Extensive experiments demonstrate that our method can surpass previous state-of-the-art methods by a large margin both quantitatively and qualitatively. In addition, to demonstrate the generality of the proposed method, we further apply it to the image deraining task, which also achieves the state-of-the-art performance. © 2019 IEEE
收录类别:EI;SCOPUS
资源类型:会议论文;期刊论文
原文链接:https://www.scopus.com/inward/record.uri?eid=2-s2.0-85063576199&doi=10.1109%2fWACV.2019.00151&partnerID=40&md5=6ebd9a2e1d44108078863f2b0b9dd4b0
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