activity
20232026
most citedDouble Trouble? Impact and Detection of Duplicates in Face Image Datasets

1 citations · 2 across the 10 of their papers we have counts for

collaborators

10 papers

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

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…

cs.CV2024★ 1 cited

Double Trouble? Impact and Detection of Duplicates in Face Image Datasets

Torsten Schlett, Christian Rathgeb, Juan Tapia +1

Various face image datasets intended for facial biometrics research were created via web-scraping, i.e. the collection of images publicly available on the internet. This work prese…

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.CV2023★ 1 cited

Privacy-preserving Multi-biometric Indexing based on Frequent Binary Patterns

Daile Osorio-Roig, Lazaro J. Gonzalez-Soler, Christian Rathgeb +1

The development of large-scale identification systems that ensure the privacy protection of enrolled subjects represents a major challenge. Biometric deployments that provide inter…

cs.CV2023

Reversing Deep Face Embeddings with Probable Privacy Protection

Daile Osorio-Roig, Paul A. Gerlitz, Christian Rathgeb +1

Generally, privacy-enhancing face recognition systems are designed to offer permanent protection of face embeddings. Recently, so-called soft-biometric privacy-enhancement approach…

cs.CV2023

Optimizing Key-Selection for Face-based One-Time Biometrics via Morphing

Daile Osorio-Roig, Mahdi Ghafourian, Christian Rathgeb +3

Nowadays, facial recognition systems are still vulnerable to adversarial attacks. These attacks vary from simple perturbations of the input image to modifying the parameters of the…