Leveraging Foundation Models for Robust and Generalizable Video-based Deepfake Detection

A novel approach that leverages the capabilities of CLIP to detect Deepfake videos through the identification of temporal affinity inconsistencies and spatial artifacts on key facial features, exhibiting superior generalization across diverse datasets.