The performance of face analysis and recognition systems depends on the quality of the
acquired face data, which is influenced by numerous factors. Automatically assessing the …

Human face recognition have been an active research area for the last few decades.
Especially, during the last five years, it has gained significant research attention from …

Achieving the upper limits of face identification accuracy in forensic applications can
minimize errors that have profound social and personal consequences. Although forensic …

Previous generations of face recognition algorithms differ in accuracy for images of different
races (race bias). Here, we present the possible underlying factors (data-driven and …

This paper studies the influence of demographics on the performance of face recognition
algorithms. The recognition accuracies of six different face recognition algorithms (three …

Deep learning models currently achieve human levels of performance on real-world face
recognition tasks. We review scientific progress in understanding human face processing …

Smartphone users have their own unique behavioral patterns when tapping on the touch
screens. These personal patterns are reflected on the different rhythm, strength, and angle …

Inspired by the primate visual system, deep convolutional neural networks (DCNNs) have
made impressive progress on the complex problem of recognizing faces across variations of …

We propose a method for face de-identification that enables fully automatic video
modification at high frame rates. The goal is to maximally decorrelate the identity, while …

Forensic facial identification examiners are required to match the identity of faces in images
that vary substantially, owing to changes in viewing conditions and in a person's …