Abstract
Generative Adversarial Networks introduces a challenging problem in the field of image generation and computer vision. Generating especially 3D face images is becoming very significant and difficult. This is openings in many interesting applications including Virtual Reality, Augmented Reality, Computer games, teleconferencing, Virtual try-on, Special effect, and so on. This paper contains three sections. The first section describes the Generative Adversarial Networks. The second section describes applications and methods and finally, the last section describes the future research directions of Generative Adversarial Networks.
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