A Review on Generative Adversarial Networks: Algorithms, Theory, and Applications

🤖 Plain-English Summary

Generative adversarial networks (GANs) have recently become a hot research topic; however, they have been studied since 2014, and a large number of algorithms have been proposed. Second, theoretical issues related to GANs are investigated.

🔑 Key Findings

• Nevertheless, few comprehensive studies explain the connections among different GAN variants and how they have evolved.
• In this paper, we attempt to provide a review of the various GAN methods from the perspectives of algorithms, theory, and applications.
• First, the motivations, mathematical representations, and structures of most GAN algorithms are introduced in detail, and we compare their commonalities and differences.

🔗 Related Resources