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New preprint on audio-visual deepfake detection across domains

EAV-DFD uses a teacher-student structure to adapt an ensemble audio-visual deepfake detector to unseen domains with only a small sample of target data.

Deepfake detectors usually lose much of their accuracy on media that does not resemble their training set. EAV-DFD recovers a large part of that gap using a teacher-student adaptation step, and reports which modality — audio or video — was manipulated.

People: Maryam Ramezani

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