TIIS (한국인터넷정보학회)
Current Result Document :
| 한글제목(Korean Title) |
Facial Feature Based Image-to-Image Translation Method |
| 영문제목(English Title) |
Facial Feature Based Image-to-Image Translation Method |
| 저자(Author) |
Shinjin Kang
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| 원문수록처(Citation) |
VOL 14 NO. 12 PP. 4835 ~ 4848 (2020. 12) |
한글내용
(Korean Abstract) |
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영문내용
(English Abstract) |
The recent expansion of the digital content market is increasing the technical demand for various facial image transformations within the virtual environment. The recent image translation technology enables changes between various domains. However, current image-toimage translation techniques do not provide stable performance through unsupervised learning, especially for shape learning in the face transition field. This is because the face is a highly sensitive feature, and the quality of the resulting image is significantly affected, especially if the transitions in the eyes, nose, and mouth are not effectively performed. We herein propose a new unsupervised method that can transform an in-wild face image into another face style through radical transformation. Specifically, the proposed method applies two face-specific feature loss functions for a generative adversarial network. The proposed technique shows that stable domain conversion to other domains is possible while maintaining the image characteristics in the eyes, nose, and mouth.
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| 키워드(Keyword) |
Game Character Generation
Character Customization
Virtual Character
Image Translation
Convolutional Neural Network
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| 파일첨부 |
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