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What is Multi-Modal Deepfake Detection Framework about?

This document presents a Multi-Modal Deepfake Detection approach that integrates audio, video, and text analysis to enhance the identification of deepfakes, achieving an AUC of 0.982, significantly outperforming unimodal and dual-modality methods. It highlights the limitations of existing detection systems and proposes a tri-modal consistency framework that checks for discrepancies across all three modalities to improve robustness against adversarial attacks. The results demonstrate that this integrated app

Author

sejal.sh.2424

Language

EN