works on

From the 1 of 17 linked papers with an AI index.

activity
20242026
collaborators

17 papers

cs.CV2026

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…

cs.LG2026

Foundation Models for Face Presentation Attack Detection: A Unified Linear-Probing Benchmark

Peter Lorenz, Anjith George, Sébastien Marcel

The paper benchmarks frozen vision foundation models for face presentation attack detection using a linear-probing protocol, finding strong intra-dataset performance but limited cr…

cs.CV2026

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…

cs.CV2026

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…

cs.CV2026

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…

cs.CV2025

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…