1 citations · 2 across the 19 of their papers we have counts for
20 papers
Learning Steadily: Accumulating Relative Point Margin Scores for Face Image Quality Assessment
Guray Ozgur, Tahar Chettaoui, Eduarda Caldeira +4
Face Image Quality Assessment determines the suitability of captured face images for automated face recognition (FR), a critical capability for reliable biometric systems. Existing…
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…
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…
AdaptDiff: Adaptive Guidance in Diffusion Models for Diverse and Identity-Consistent Face Synthesis (Student Abstract)
Eduarda Caldeira, Tahar Chettaoui, Naser Damer +1
Diffusion models conditioned on identity embeddings enable the generation of synthetic face images that consistently preserve identity across multiple samples. Recent work has show…
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…
ViTNT-FIQA: Training-Free Face Image Quality Assessment with Vision Transformers
Guray Ozgur, Eduarda Caldeira, Tahar Chettaoui +4
Face Image Quality Assessment (FIQA) is essential for reliable face recognition systems. Current approaches primarily exploit only final-layer representations, while training-free…
NegFaceDiff: The Power of Negative Context in Identity-Conditioned Diffusion for Synthetic Face Generation
Eduarda Caldeira, Naser Damer, Fadi Boutros
The use of synthetic data as an alternative to authentic datasets in face recognition (FR) development has gained significant attention, addressing privacy, ethical, and practical…
MADPromptS: Unlocking Zero-Shot Morphing Attack Detection with Multiple Prompt Aggregation
Eduarda Caldeira, Fadi Boutros, Naser Damer
Face Morphing Attack Detection (MAD) is a critical challenge in face recognition security, where attackers can fool systems by interpolating the identity information of two or more…
DiffProb: Data Pruning for Face Recognition
Eduarda Caldeira, Jan Niklas Kolf, Naser Damer +1
Face recognition models have made substantial progress due to advances in deep learning and the availability of large-scale datasets. However, reliance on massive annotated dataset…
MADation: Face Morphing Attack Detection with Foundation Models
Eduarda Caldeira, Guray Ozgur, Tahar Chettaoui +5
Despite the considerable performance improvements of face recognition algorithms in recent years, the same scientific advances responsible for this progress can also be used to cre…
FoundPAD: Foundation Models Reloaded for Face Presentation Attack Detection
Guray Ozgur, Eduarda Caldeira, Tahar Chettaoui +3
Although face recognition systems have seen a massive performance enhancement in recent years, they are still targeted by threats such as presentation attacks, leading to the need…
MST-KD: Multiple Specialized Teachers Knowledge Distillation for Fair Face Recognition
Eduarda Caldeira, Jaime S. Cardoso, Ana F. Sequeira +1
As in school, one teacher to cover all subjects is insufficient to distill equally robust information to a student. Hence, each subject is taught by a highly specialised teacher. F…
Model Compression Techniques in Biometrics Applications: A Survey
Eduarda Caldeira, Pedro C. Neto, Marco Huber +2
The development of deep learning algorithms has extensively empowered humanity's task automatization capacity. However, the huge improvement in the performance of these models is h…
Compressed Models Decompress Race Biases: What Quantized Models Forget for Fair Face Recognition
Pedro C. Neto, Eduarda Caldeira, Jaime S. Cardoso +1
With the ever-growing complexity of deep learning models for face recognition, it becomes hard to deploy these systems in real life. Researchers have two options: 1) use smaller mo…
Unveiling the Two-Faced Truth: Disentangling Morphed Identities for Face Morphing Detection
Eduarda Caldeira, Pedro C. Neto, Tiago Gonçalves +3
Morphing attacks keep threatening biometric systems, especially face recognition systems. Over time they have become simpler to perform and more realistic, as such, the usage of de…