COMPOUND MULTI-BRANCH FEATURE FUSION FOR IMAGE DERAINDROP

被引：5
|
作者：
Fan, Chi-Mao [1 ,2 ]
Liu, Tsung-Jung [1 ,2 ]
Liu, Kuan-Hsien [3 ]
机构：
[1] Natl Chung Hsing Univ, Dept Elect Engn, Taichung, Taiwan
[2] Natl Chung Hsing Univ, Grad Inst Commun Engn, Taichung, Taiwan
[3] Natl Taichung Univ Sci & Technol, Dept Comp Sci & Informat Engn, Taichung, Taiwan
来源：
2023 IEEE INTERNATIONAL CONFERENCE ON IMAGE PROCESSING, ICIP | 2023年
关键词：
Image restoration; deraining; deraindrop; branch network; mixed skip connection; QUALITY ASSESSMENT;
D O I：
10.1109/ICIP49359.2023.10222907
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
Image restoration is a challenging and ill-posed problem which also has been a long-standing issue. In this paper, we proposed a multi-branch restoration model inspired from the Human Visual System (i.e., Retinal Ganglion Cells) for image deraindrop. The experiments show that the proposed multi-branch architecture, called CMFNet, has state-of-the-art performance results. The source code and pretrained models are available at https: //github.com/FanChiMao/CMFNet. And the interactive demonstration of the proposed deraindrop model can be accessed at https://reurl.cc/dXaeNg.
引用
收藏
页码：3399 / 3403
页数：5
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