Frontal Face Generation Algorithm from Multi-view Images Based on Generative Adversarial NetworkFrontal Face Generation Algorithm from Multi-view Images Based on Generative Adversarial Network
- Other Titles
- Frontal Face Generation Algorithm from Multi-view Images Based on Generative Adversarial Network
- Authors
- 허영진; 김병규; Partha Pratim Roy
- Issue Date
- Jun-2021
- Publisher
- 한국멀티미디어학회
- Keywords
- GAN; StyleGAN; cGAN; Deep learning; Classification; Frontal face
- Citation
- Journal of Multimedia Information System, v.8, no.2, pp 85 - 92
- Pages
- 8
- Journal Title
- Journal of Multimedia Information System
- Volume
- 8
- Number
- 2
- Start Page
- 85
- End Page
- 92
- URI
- https://scholarworks.sookmyung.ac.kr/handle/2020.sw.sookmyung/146167
- DOI
- 10.33851/JMIS.2021.8.2.85
- ISSN
- 2383-7632
- Abstract
- In a face, there is much information of person's identity. Because of this property, various tasks such as expression recognition, identity recognition and deepfake have been actively conducted. Most of them use the exact frontal view of the given face. However, various directions of the face can be observed rather than the exact frontal image in real situation. The profile (side view) lacks information when comparing with the frontal view image. Therefore, if we can generate the frontal face from other directions, we can obtain more information on the given face. In this paper, we propose a combined style model based the conditional generative adversarial network (cGAN) for generating the frontal face from multi-view images that consist of characteristics that not only includes the style around the face (hair and beard) but also detailed areas (eye, nose, and mouth).
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