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 …

The informativeness of data has always been of great interest within the machine learning
community. Nowadays, with the skyrocketing advancement of artificial intelligence and …

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 …

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

State-of-the-art face recognition models are computationally expensive for mobile
applications. Training lightweight face recognition models also requires large identity …

In this paper we examine how pre-processing and training methods impact on the
performance of Lightweight CNNs through evaluations on MobileNetV3 with a spoofing …

Current periocular and face recognition approaches utilize computationally costly deep
neural networks, achieving notable recognition accuracies. Deploying such solutions in …

As violent criminals, such as child sex offenders, tend to have high recidivism rates in
modern society, there is a need to prevent such offenders from approaching socially …

This paper presents a comprehensive overview of Convolutional Neural Networks (CNNs) in
the context of face recognition. By analyzing 150 research papers, we investigate major …

Face recognition has achieved outstanding performance in the last decade with the
development of deep learning techniques. Nowadays, the challenges in face recognition are …