FISS GAN: A Generative Adversarial Network for Foggy Image Semantic Segmentation
文献类型：期刊论文
| 作者 | Kunhua Liu; Zihao Ye; Hongyan Guo; Dongpu Cao; Long Chen ; Fei-Yue Wang
|
| 刊名 | IEEE/CAA Journal of Automatica Sinica
 |
| 出版日期 | 2021 |
| 卷号 | 8期号:8页码:1428-1439 |
| 关键词 | Edge GAN foggy images foggy image semantic segmentation GAN semantic segmentation |
| ISSN号 | 2329-9266 |
| DOI | 10.1109/JAS.2021.1004057 |
| 英文摘要 | Because pixel values of foggy images are irregularly higher than those of images captured in normal weather (clear images), it is difficult to extract and express their texture. No method has previously been developed to directly explore the relationship between foggy images and semantic segmentation images. We investigated this relationship and propose a generative adversarial network (GAN) for foggy image semantic segmentation (FISS GAN), which contains two parts: an edge GAN and a semantic segmentation GAN. The edge GAN is designed to generate edge information from foggy images to provide auxiliary information to the semantic segmentation GAN. The semantic segmentation GAN is designed to extract and express the texture of foggy images and generate semantic segmentation images. Experiments on foggy cityscapes datasets and foggy driving datasets indicated that FISS GAN achieved state-of-the-art performance. |
| 源URL | [http://ir.ia.ac.cn/handle/173211/44594]  |
| 专题 | 自动化研究所_学术期刊_IEEE/CAA Journal of Automatica Sinica |
| 推荐引用方式 GB/T 7714 | Kunhua Liu,Zihao Ye,Hongyan Guo,et al. FISS GAN: A Generative Adversarial Network for Foggy Image Semantic Segmentation[J]. IEEE/CAA Journal of Automatica Sinica,2021,8(8):1428-1439. |
| APA | Kunhua Liu,Zihao Ye,Hongyan Guo,Dongpu Cao,Long Chen,&Fei-Yue Wang.(2021).FISS GAN: A Generative Adversarial Network for Foggy Image Semantic Segmentation.IEEE/CAA Journal of Automatica Sinica,8(8),1428-1439. |
| MLA | Kunhua Liu,et al."FISS GAN: A Generative Adversarial Network for Foggy Image Semantic Segmentation".IEEE/CAA Journal of Automatica Sinica 8.8(2021):1428-1439. |
入库方式： OAI收割
来源：自动化研究所
浏览0
下载0
收藏0
其他版本
除非特别说明，本系统中所有内容都受版权保护，并保留所有权利。