Ming Xu

Enhancing robustness in deepfake detection: a contrastive invariance approach

A detection framework based on noise-invariant contrastive learning to enhance adversarial robustness by aligning feature representations of original and noise-augmented samples, which significantly outperforms conventional adversarial training.