Beyond Ambiguous Visual Cues: Studying Physiological Disruptions and Cross-Modal Inconsistencies in Deepfake Videos
This paper constructs high-fidelity deepfake manipulations on established real rPPG datasets to investigate how forgeries disrupt natural physiological signals and facial behavior at the same time and proposes a bidirectional co-attention fusion detector that jointly models rPPG and facial behavior tokens.