A Survey of Deepfake Detection Methods
The methodologies used for deepfake detection using computer vision and deep learning on currently available datasets are evaluated and the results are presented in a comprehensive manner.
Abstract
In this work, we examine recent methods employed for detecting deepfake images and videos, which have become increasingly prevalent in recent times. Deepfake datasets are categorized into generations based on the number of data, quality, and diversity of the data they contain, and a new realistic dataset has been generated to accurately reflect real-world conditions. In this paper, we evaluate the methodologies used for deepfake detection using computer vision and deep learning on currently available datasets and present the results in a comprehensive manner.