摘要
In this study, we propose a new synthetic fog generation network (SFG-Net), which employs the two-stream image-to-image translation model as a base backbone and integrates a self-attention (SA) module for generating foggy images. With the presence of the SA module between the style pipeline and generator of the proposed SFG-Net, the style structure from style features of the input images is captured to advance the image translation performance. Experimental results show the effectiveness of the proposed SFG-Net in both quantitative evaluations and perceptual quality compared with the competitive method.
| 原文 | English |
|---|---|
| 主出版物標題 | Proceedings - 2022 IEEE International Conference on Consumer Electronics - Taiwan, ICCE-Taiwan 2022 |
| 發行者 | Institute of Electrical and Electronics Engineers Inc. |
| 頁面 | 435-436 |
| 頁數 | 2 |
| ISBN(電子) | 9781665470506 |
| DOIs | |
| 出版狀態 | Published - 2022 |
| 事件 | 2022 IEEE International Conference on Consumer Electronics - Taiwan, ICCE-Taiwan 2022 - Taipei, Taiwan 持續時間: 6 7月 2022 → 8 7月 2022 |
出版系列
| 名字 | Proceedings - 2022 IEEE International Conference on Consumer Electronics - Taiwan, ICCE-Taiwan 2022 |
|---|
Conference
| Conference | 2022 IEEE International Conference on Consumer Electronics - Taiwan, ICCE-Taiwan 2022 |
|---|---|
| 國家/地區 | Taiwan |
| 城市 | Taipei |
| 期間 | 6/07/22 → 8/07/22 |
文獻附註
Publisher Copyright:© 2022 IEEE.
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