Finally, many researchers consider unsupervised learning as the missing link in general AI systems. To overcome these obstacles, attempts to solve established problems using less labeled data is key. In this scenario, GANs pose a real alternative for learning complicated tasks with less labeled samples. Yet, the performance gap between supervised and semi-supervised learning is still far from being equal. We can certainly expect this gap to become shorter as new approaches come into play.