N. Damer

EXPL-FR reveals that you can achieve interpretable face recognition without any text training, using a simple adapter to bridge vision and language spaces.

Transferable presentation attack representations can be learned without relying on facial content, achieving high performance across standard benchmarks.

Face recognition systems, beware: DCMorph's dual-stream diffusion morphs achieve unprecedented attack success rates while remaining stealthy to existing detection methods.

Forget relying solely on final-layer features: intermediate layers in Vision Transformers hold untapped potential for boosting face image quality assessment.

Turns out, your pre-trained face recognition ViT already knows which faces are high quality, just by looking at the attention maps.