7 citations · 13 across the 21 of their papers we have counts for
28 papers · 1 filter
Foundation and Multimodal Large Language Models for Face Presentation and Morph Attack Detection
Hatef Otroshi Shahreza, Asif Hussain Khan, Peter Lorenz +2
Face recognition systems are increasingly deployed in security-critical applications, yet they remain vulnerable to presentation and morph attacks. Presentation attack detection (P…
Improving Low-Resolution Face Recognition under Limited Data: How Synthetic Data Generation Can Close the Domain Gap
Luis S. Luevano, Ünsal Öztürk, Hatef Otroshi Shahreza +2
Face Recognition (FR) systems in surveillance settings often encounter Low Resolution (LR) faces, those whose face region falls below the standard 112 112 input size. Whil…
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…
Demographic Fairness in Multimodal LLMs: A Benchmark of Gender and Ethnicity Bias in Face Verification
Ünsal Öztürk, Hatef Otroshi Shahreza, Sébastien Marcel
Multimodal Large Language Models (MLLMs) have recently been explored as face verification systems that determine whether two face images are of the same person. Unlike dedicated fa…
Evaluating Multimodal Large Language Models for Heterogeneous Face Recognition
Hatef Otroshi Shahreza, Anjith George, Sébastien Marcel
Multimodal Large Language Models (MLLMs) have recently demonstrated strong performance on a wide range of vision-language tasks, raising interest in their potential use for biometr…
Benchmarking Multimodal Large Language Models for Face Recognition
Hatef Otroshi Shahreza, Sébastien Marcel
Multimodal large language models (MLLMs) have achieved remarkable performance across diverse vision-and-language tasks. However, their potential in face recognition remains underex…