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Eyebrow Recognition for Identifying Deepfake Videos

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dc.contributor.authorNguyen, Hoang (Mark)
dc.contributor.authorDerakhshani, Reza
dc.contributor.editorBrömme, Arslan
dc.contributor.editorBusch, Christoph
dc.contributor.editorDantcheva, Antitza
dc.contributor.editorRaja, Kiran
dc.contributor.editorRathgeb, Christian
dc.contributor.editorUhl, Andreas
dc.date.accessioned2020-09-16T08:25:45Z
dc.date.available2020-09-16T08:25:45Z
dc.date.issued2020
dc.description.abstractDeepfake 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.en
dc.identifier.isbn978-3-88579-700-5
dc.identifier.pissn1617-5468
dc.identifier.urihttps://dl.gi.de/handle/20.500.12116/34328
dc.language.isoen
dc.publisherGesellschaft für Informatik e.V.
dc.relation.ispartofBIOSIG 2020 - Proceedings of the 19th International Conference of the Biometrics Special Interest Group
dc.relation.ispartofseriesLecture Notes in Informatics (LNI) - Proceedings, Volume P-306
dc.subjectDeepfake detection
dc.subjecteyebrow biometrics
dc.subjectbiometric recognition
dc.titleEyebrow Recognition for Identifying Deepfake Videosen
dc.typeText/Conference Paper
gi.citation.endPage206
gi.citation.publisherPlaceBonn
gi.citation.startPage199
gi.conference.date16.-18. September 2020
gi.conference.locationInternational Digital Conference
gi.conference.sessiontitleFurther Conference Contributions

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P306 - BIOSIG 2020 - Proceedings of the 19th International Conference of the Biometrics Special Interest Group