期刊論文
| 學年 | 109 |
|---|---|
| 學期 | 2 |
| 出版（發表）日期 | 2021-02-01 |
| 作品名稱 | Multi-style image transfer system using conditional cycleGAN |
| 作品名稱（其他語言） | |
| 著者 | Tu, Ching-Ting; Lin, Hwei Jen; Tsia, Yihjia |
| 單位 | |
| 出版者 | |
| 著錄名稱、卷期、頁數 | The Imaging Science Journal |
| 摘要 | This paper aims to extend the capability of Cycle-Consistent Adversarial Network (CycleGAN) by equipping it with a conditional constraint and extend it into a multi-style image transfer system that can transfer images among more than two image domains. The conditional constraint is given in the form of the target style feature map instead of a one-hot vector, and has shown to provide better transfer results. The proposed system offers greater flexibility for users to choose the style for image transfer. Experimental results show that such an architecture is not only feasible but also yields good results. The proposed architecture can be extended to other transformation applications, such as facial expressions transfer, face aging, and synthesis of various features. |
| 關鍵字 | Convolutional neural network (CNN);deep learning;generative adversarial net (GAN);conditional GAN (CGAN);CycleGAN;conditional CycleGAN;PatchGAN;image style transfer |
| 語言 | en_US |
| ISSN | 1368-2199 |
| 期刊性質 | 國外 |
| 收錄於 | |
| 產學合作 | |
| 通訊作者 | |
| 審稿制度 | 否 |
| 國別 | GBR |
| 公開徵稿 | |
| 出版型式 | ,電子版,紙本 |
| 相關連結 |
機構典藏連結 ( http://tkuir.lib.tku.edu.tw:8080/dspace/handle/987654321/120393 ) |