DFCON: Attention-Driven Supervised Contrastive Learning for Robust Deepfake Detection
We propose DFCON, a supervised contrastive learning and ensemble-based approach for robust deepfake detection, achieving 95.83% validation accuracy in IEEE SP Cup 2025.
Jan 28, 2025
