11 papers
IJCB-AFMFR 2026: Competition on Adapting Foundation Models for Face Recognition Using Synthetic Training Data
Tahar Chettaoui, Guray Ozgur, Eduarda Caldeira +13
This paper presents a summary of the Competition on Adapting Foundation Models for Face Recognition Using Synthetic Training Data (AFMFR), held at the 2026 International Joint Conf…
Vision Transformers for Face Recognition Need More Registers
Tahar Chettaoui, Guray Ozgur, Eduarda Caldeira +2
Recent advances in Vision Transformers (ViTs) for face recognition (FR) have moved beyond the standard CLS-token paradigm. In this paradigm, a special classification token (CLS) is…
ViT-FREE: Efficient Face Recognition via Early Exiting and Synthetic Adaptation
Tahar Chettaoui, Guray Ozgur, Eduarda Caldeira +2
Vision Transformers (ViTs) have gained significant attention in computer vision and shown strong potential for face recognition (FR). However, their high computational cost makes d…
PreFIQs: Face Image Quality Is What Survives Pruning
Jan Niklas Kolf, Guray Ozgur, Andrea Atzori +4
Face Image Quality Assessment (FIQA) evaluates the utility of a face image for automated face recognition (FR) systems. In this work, we propose PreFIQs, an unsupervised and traini…
DCMorph: Face Morphing via Dual-Stream Cross-Attention Diffusion
Tahar Chettaoui, Eduarda Caldeira, Guray Ozgur +3
Advancing face morphing attack techniques is crucial to anticipate evolving threats and develop robust defensive mechanisms for identity verification systems. This work introduces…
On the Impact of Face Segmentation-Based Background Removal on Recognition and Morphing Attack Detection
Eduarda Caldeira, Guray Ozgur, Fadi Boutros +1
This study investigates the impact of face image background correction through segmentation on face recognition and morphing attack detection performance in realistic, unconstraine…