TY - CHAP
T1 - DeepFake Detection
AU - Lyu, Siwei
N1 - Publisher Copyright:
© 2022, The Author(s).
PY - 2022
Y1 - 2022
N2 - One particular disconcerting form of disinformation are the impersonating audios/videos backed by advanced AI technologies, in particular, deep neural networks (DNNs). These media forgeries are commonly known as the DeepFakes. The AI-based tools are making it easier and faster than ever to create compelling fakes that are challenging to spot. While there are interesting and creative applications of this technology, it can be weaponized to cause negative consequences. In this chapter, we survey the state-of-the-art DeepFake detection methods.
AB - One particular disconcerting form of disinformation are the impersonating audios/videos backed by advanced AI technologies, in particular, deep neural networks (DNNs). These media forgeries are commonly known as the DeepFakes. The AI-based tools are making it easier and faster than ever to create compelling fakes that are challenging to spot. While there are interesting and creative applications of this technology, it can be weaponized to cause negative consequences. In this chapter, we survey the state-of-the-art DeepFake detection methods.
UR - https://www.scopus.com/pages/publications/85127852244
U2 - 10.1007/978-981-16-7621-5_12
DO - 10.1007/978-981-16-7621-5_12
M3 - Chapter
AN - SCOPUS:85127852244
T3 - Advances in Computer Vision and Pattern Recognition
SP - 313
EP - 331
BT - Advances in Computer Vision and Pattern Recognition
PB - Springer Science and Business Media Deutschland GmbH
ER -