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http://dx.doi.org/10.7583/JKGS.2021.21.3.13

A GAN-based face rotation technique using 3D face model for game characters  

Kim, Handong (Dept. of Computer Science, Graduate school, Sangmyung Univ.)
Han, Jongdae (Dept. of Computer Science, Sangmyung Univ.)
Yang, Heekyung (Dept. of SW Convergence, Sangmyung Univ.)
Min, Kyungha (Dept. of Computer Science, Sangmyung Univ.)
Publication Information
Journal of Korea Game Society / v.21, no.3, 2021 , pp. 13-24 More about this Journal
Abstract
This paper shows the face rotation applicable to game character facial illustration. Existing studies limited data to human face data, required a large amount of data, and the synthesized results were not good. In this paper, the following method was introduced to solve the existing problems of existing studies. First, a 3D model with features of the input image was rotated and then rendered as a 2D image to construct a data set. Second, by designing GAN that can learn features of various poses from the data built through the 3D model, the input image can be synthesized at a desired pose. This paper presents the results of synthesizing the game character face illustration. From the synthesized result, it can be confirmed that the proposed method works well.
Keywords
Game illustration; Deep learning;
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