Challenges and Applications of Face Deepfake

Citations

WEB OF SCIENCE

10
Citations

SCOPUS

11

초록

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.

키워드

Deepfake; DeepFake creation; Faceswap; Face attribute editing; Deepfake dataset
제목
Challenges and Applications of Face Deepfake
저자
Laishram, Lamyanba; Rahman, Md Maklachur; Jung, Soon Ki
DOI
10.1007/978-3-030-81638-4_11
발행일
2021
유형
Proceedings Paper
저널명
Communications in Computer and Information Science
권
1405
페이지
131 ~ 156