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

页码：3399 / 3403

页数：5

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