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Unit-Selection Based Facial Video Manipulation Detection
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Datum
2020
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Verlag
Gesellschaft für Informatik e.V.
Zusammenfassung
Advancements in video synthesis technology have caused major concerns over the authenticity
of audio-visual content. A video manipulation method that is often overlooked is inter-frame
forgery, in which segments (or units) of an original video are reordered and rejoined while cut-points
are covered with transition effects. Subjective tests have shown the susceptibility of viewers in mistaking
such content as authentic. In order to support research on the detection of such manipulations,
we introduce a large-scale dataset of 1000 morph-cut videos that were generated by automation of
the popular video editing software Adobe Premiere Pro. Furthermore, we propose a novel differential
detection pipeline and achieve an outstanding frame-level detection accuracy of 95%.