Generative Adversarial Networks: a systematic review and applications

Abstract

Since their introduction in 2014 Generative Adversarial Networks (GANs) have been employed successfully in many areas such as image processing, computer vision, medical imaging, video as well as other disciplines. A large number of review papers have been published, focusing on certain application areas and proposed methods. In this paper, we collected the most recent review papers, organized the collected information according to the application field and we presented the application areas, the GAN architectures that have been applied in each case and summarized the open issues in each area.