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cs.CV2026

Vision Language Model Fusion for Explainable Face Recognition

Ana Estrada-Real, Lydia Alapatt, Christoph Busch +1

Responsible deployment of face verification systems requires more than accurate decisions: systems should also provide interpretable and auditable evidence that enables users to un…

cs.CV2026

Optimizing Image Preparation and Compression for Face Recognition within 1024 Bytes

Paul Andreas, Torsten Schlett, Christoph Busch

ICAO-compliant machine readable travel documents enable automated biometric face verification. The biometric reference is stored on an RFID chip included in form of a JPEG or JPEG…

cs.CV2026

Detection of T-shirt Presentation Attacks in Face Recognition Systems

Mathias Ibsen, Loris Tim Ide, Christian Rathgeb +1

Face recognition systems are often used for biometric authentication. Nevertheless, it is known that without any protective measures, face recognition systems are vulnerable to pre…

cs.CV2026

DifFoundMAD: Foundation Models meet Differential Morphing Attack Detection

Lazaro J. Gonzalez-Soler, André Dörsch, Christian Rathgeb +1

In this work, we introduce DifFoundMAD, a parameter-efficient D-MAD framework that exploits the generalisation capabilities of vision foundation models (FM) to capture discrepancie…

cs.CV2024

TetraLoss: Improving the Robustness of Face Recognition against Morphing Attacks

Mathias Ibsen, Lázaro J. González-Soler, Christian Rathgeb +1

Face recognition systems are widely deployed in high-security applications such as for biometric verification at border controls. Despite their high accuracy on pristine data, it i…

cs.CV2024

Fairness measures for biometric quality assessment

André Dörsch, Torsten Schlett, Peter Munch +2

Quality assessment algorithms measure the quality of a captured biometric sample. Since the sample quality strongly affects the recognition performance of a biometric system, it is…