Every Frame You Take: The Video-based Morphing Attack Detection Challenge
N. Di, Lorenzo Pellegrini, Simone Maurizio et al.
· 0 citations
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Jul 2026
Foundation Models for Face Presentation Attack Detection: A Unified Linear-Probing Benchmark
It is suggested that while pretrained representations contain PAD-relevant information, explicit adaptation remains necessary to address domain shift.
P. Lorenz, Anjith George, Sébastien Marcel
· arXiv.org · 1 citation
Preprint
Aug 2026
Foundation and Multimodal Large Language Models for Face Presentation and Morph Attack Detection
The experiments show that FMs and MLLMs can achieve significant performance for PAD and MAD and the fine-tuned models achieve state-of-the-art detection performance in cross-dataset evaluation, indicating that general-purpose pretrained representations carry substantial attack-relevant information.
H. O. Shahreza, A. H. Khan, P. Lorenz et al.
· 0 citations