activity
20152024
most citedBiometric Face Presentation Attack Detection with Multi-Channel Convolutional Neural Network

269 citations · 721 across the 25 of their papers we have counts for

collaborators

30 papers

cs.CV2024★ 4 cited

From Modalities to Styles: Rethinking the Domain Gap in Heterogeneous Face Recognition

Anjith George, Sebastien Marcel

Heterogeneous Face Recognition (HFR) focuses on matching faces from different domains, for instance, thermal to visible images, making Face Recognition (FR) systems more versatile…

cs.CV2023

SynthDistill: Face Recognition with Knowledge Distillation from Synthetic Data

Hatef Otroshi Shahreza, Anjith George, Sébastien Marcel

State-of-the-art face recognition networks are often computationally expensive and cannot be used for mobile applications. Training lightweight face recognition models also require…

cs.CV2023

EFaR 2023: Efficient Face Recognition Competition

Jan Niklas Kolf, Fadi Boutros, Jurek Elliesen +24

This paper presents the summary of the Efficient Face Recognition Competition (EFaR) held at the 2023 International Joint Conference on Biometrics (IJCB 2023). The competition rece…

cs.CV2023

Bridging the Gap: Heterogeneous Face Recognition with Conditional Adaptive Instance Modulation

Anjith George, Sebastien Marcel

Heterogeneous Face Recognition (HFR) aims to match face images across different domains, such as thermal and visible spectra, expanding the applicability of Face Recognition (FR) s…

cs.CV2023

EdgeFace: Efficient Face Recognition Model for Edge Devices

Anjith George, Christophe Ecabert, Hatef Otroshi Shahreza +2

In this paper, we present EdgeFace, a lightweight and efficient face recognition network inspired by the hybrid architecture of EdgeNeXt. By effectively combining the strengths of…

cs.CV2022★ 11 cited

Attacking Face Recognition with T-shirts: Database, Vulnerability Assessment and Detection

M. Ibsen, C. Rathgeb, F. Brechtel +5

Face recognition systems are widely deployed for biometric authentication. Despite this, it is well-known that, without any safeguards, face recognition systems are highly vulnerab…