Photo-to-Manga Faces Translation Based Conditional Generative Adversarial Networks
-
- HATAKEYAMA Taro
- Keio University
-
- SAITO Ryusuke
- Keio University
-
- HIRUTA Komei
- Keio University
-
- HASHIMOTO Atsushi
- Keio University OMRON SINIC X Corp.
-
- KURIHARA Satoshi
- Keio University
Bibliographic Information
- Other Title
-
- 条件付き敵対的生成ネットワークを使用した実写顔画像から漫画顔画像への変換
Abstract
<p>Manga is one of the representative cultures of Japan. In general, manga artists depict characters with black lines on a white background and describe their appearance and movements abstractly, while exaggerating their characteristics geometrically. Aiming to reproduce such information processing capabilities of humans computationally, we propose Conditional GAN Inversion, which is the application of GAN Inversion to Conditional GAN, to realize the translation from photos to manga faces. Conditional GAN learns multiple domains in a shared network. It enables geometrically large deformations and the preservation of the identity of original images. Experimental results show that our method generates high-quality manga faces preserving the drawing style and the identities compared to other related state-of-the-art methods.</p>
Journal
-
- Proceedings of the Annual Conference of JSAI
-
Proceedings of the Annual Conference of JSAI JSAI2022 (0), 1O1GS701-1O1GS701, 2022
The Japanese Society for Artificial Intelligence
- Tweet
Details 詳細情報について
-
- CRID
- 1390855656024597120
-
- Text Lang
- ja
-
- Data Source
-
- JaLC
-
- Abstract License Flag
- Disallowed