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Eyebrow Recognition for Identifying Deepfake Videos
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Datum
2020
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Gesellschaft für Informatik e.V.
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.