Analyzing the Methods for Detecting Deepfakes
This document finds DEFAKEHOP as the best method in deepfake detection, which uses spatial dimensionality reduction and soft classification to obtain a more concise description of the face for each detection channel.
Abstract
Progress in the field of deep counterfeiting is equally impressive and worrisome on the upside. We can change the fidelity of the media that will undoubtedly lead to some world memes, but in the hands of the bad guys. Deepfake technology can be used to spread misinformation and destroy public trust in. It is almost like science fiction identity theft. You can allow anyone to tell what they want, but the reverse is true. In this paper, Detailed study has been carried out that proposed different deepfake detection models, this document finds DEFAKEHOP as the best method in , which uses spatial dimensionality reduction and soft classification to obtain a more concise description of the face for each detection channel. This article finally looks at ’s research direction in this field, as well as the development of more powerful technologies to deal with the growing threat surrounding Deepfake technology.