Eyebrow Recognition for Identifying Deepfake Videos

Zusammenfassung
Deepfake imagery that contains altered faces has become a threat to online content. Current anti-deepfake approaches usually do so by detecting image anomalies, such as visible artifacts or inconsistencies. However, with deepfake advances, these visual artifacts are becoming harder to detect. In this paper, we show that one can use biometric eyebrow matching as a tool to detect manipulated faces. Our method could provide an 0.88 AUC and 20.7% EER for deepfake detection when applied to the highest quality deepfake dataset, Celeb-DF.
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  • BibTeX
Nguyen, H. (. & Derakhshani, R., (2020). Eyebrow Recognition for Identifying Deepfake Videos. In: Brömme, A., Busch, C., Dantcheva, A., Raja, K., Rathgeb, C. & Uhl, A. (Hrsg.), BIOSIG 2020 - Proceedings of the 19th International Conference of the Biometrics Special Interest Group. Bonn: Gesellschaft für Informatik e.V.. (S. 199-206).
@inproceedings{mci/Nguyen2020,
author = {Nguyen, Hoang (Mark) AND Derakhshani, Reza},
title = {Eyebrow Recognition for Identifying Deepfake Videos},
booktitle = {BIOSIG 2020 - Proceedings of the 19th International Conference of the Biometrics Special Interest Group},
year = {2020},
editor = {Brömme, Arslan AND Busch, Christoph AND Dantcheva, Antitza AND Raja, Kiran AND Rathgeb, Christian AND Uhl, Andreas} ,
pages = { 199-206 },
publisher = {Gesellschaft für Informatik e.V.},
address = {Bonn}
}
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ISBN: 978-3-88579-700-5
ISSN: 1617-5468
Datum: 2020
Sprache: en (en)
Typ: Text/Conference Paper
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