Challenges and Applications of Face Deepfake

Published: 01 Jan 2021, Last Modified: 15 Jul 2025IW-FCV 2021EveryoneRevisionsBibTeXCC BY-SA 4.0
Abstract: With the development of Generative deep learning algorithms in the last decade, it has become increasingly difficult to differentiate between what is real and what is fake. With the easily available “Deepfake” applications, even a person with less computing knowledge can also produce realistic Deepfake data. These fake data have many benefits while on the other hand, it can also be used for unethical and malicious purposes. Deepfake can be anything fake data generated by using deep learning methods. In this study, we focus on Deepfake with respect to face manipulation. We represent the currently used algorithms and datasets are represented for creating Deepfake. We also study the challenges and the real-world applications in which the benefits, as well as the drawbacks of using Deepfake, are being pointed out.
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