• KSII Transactions on Internet and Information Systems
    Monthly Online Journal (eISSN: 1976-7277)

Facial Feature Based Image-to-Image Translation Method

Vol. 14, No. 12, December 31, 2020
10.3837/tiis.2020.12.012, Download Paper (Free):

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-to-image 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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Cite this article

[IEEE Style]
S. Kang, "Facial Feature Based Image-to-Image Translation Method," KSII Transactions on Internet and Information Systems, vol. 14, no. 12, pp. 4835-4848, 2020. DOI: 10.3837/tiis.2020.12.012.

[ACM Style]
Shinjin Kang. 2020. Facial Feature Based Image-to-Image Translation Method. KSII Transactions on Internet and Information Systems, 14, 12, (2020), 4835-4848. DOI: 10.3837/tiis.2020.12.012.