LAUSR

Deep Fake technology has developed rapidly in its generation and detection in recent years. Researchers in both fields are outpacing each other in their axes achievements. The works use, among other methods, autoencoders, generative adversarial networks, or other algorithms to create fake content that is resistant to detection by algorithms or the human eye. Among the ever-increasing number of emerging works, a few can be singled out that, in their solutions and robustness of detection, contribute significantly to the field. Despite the advancement of emerging generative algorithms, the fields are still left for further research. This paper will briefly introduce the fundamentals of some the latest Face Swap Deep Fake algorithms.