12 papers · 1 filter
Tomatoes, Potatoes, and Onions: Questioning the Need for Faces in Face Presentation Attack Detection
Guray Ozgur, Fadi Boutros, Naser Damer
Face presentation attack detection (PAD) is traditionally formulated as a face-specific problem, although many of the visual artifacts introduced by print, replay, and recapture pr…
EXPL-FR: Explaining Face Recognition Models via Vision-Language Alignment
Guray Ozgur, Mustafa Efe Tamyapar, Naser Damer +1
Deep face recognition (FR) models reach near-saturated accuracy but remain opaque: a practitioner cannot ask which semantic attributes a similarity score relied upon. EXPL-FR answe…
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…
FunFace: Feature Utility and Norm Estimation for Face Recognition
Žiga Babnik, Fadi Boutros, Naser Damer +3
Face Recognition (FR) is used in a variety of application domains, from entertainment and banking to security and surveillance. Such applications rely on the FR model to be robust…
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…
EX-FIQA: Leveraging Intermediate Early eXit Representations from Vision Transformers for Face Image Quality Assessment
Guray Ozgur, Tahar Chettaoui, Eduarda Caldeira +4
Face Image Quality Assessment is crucial for reliable face recognition systems, yet existing Vision Transformer-based approaches rely exclusively on final-layer representations, ig…
ATTN-FIQA: Interpretable Attention-based Face Image Quality Assessment with Vision Transformers
Guray Ozgur, Tahar Chettaoui, Eduarda Caldeira +5
Face Image Quality Assessment (FIQA) aims to assess the recognition utility of face samples and is essential for reliable face recognition (FR) systems. Existing approaches require…
IDperturb: Enhancing Variation in Synthetic Face Generation via Angular Perturbation
Fadi Boutros, Eduarda Caldeira, Tahar Chettaoui +1
Synthetic data has emerged as a practical alternative to authentic face datasets for training face recognition (FR) systems, especially as privacy and legal concerns increasingly r…