3D face reconstruction algorithms from images and videos are applied to many fields, from
plastic surgery to the entertainment sector, thanks to their advantageous features. However …

The increasing digitization and datification of all aspects of people's daily life, and the
consequent growth in the use of personal data, are increasingly challenging the current …

Computer Vision (CV) has achieved remarkable results, outperforming humans in several
tasks. Nonetheless, it may result in significant discrimination if not handled properly. Indeed …

Over the past two decades, biometric recognition has exploded into a plethora of different
applications around the globe. This proliferation can be attributed to the high levels of …

The great advancements of generative adversarial networks and face recognition models in
computer vision have made it possible to swap identities on images from single sources …

This article presents FRCSyn-onGoing, an ongoing challenge for face recognition where
researchers can easily benchmark their systems against the state of the art in an open …

In this work, we propose QMagFace, a simple and effective face recognition solution
(QMagFace) that combines a quality-aware comparison score with a recognition model …

We explore varying face recognition accuracy across demographic groups as a
phenomenon partly caused by differences in face illumination. We observe that for a …

Face benchmarks empower the research community to train and evaluate high-performance
face recognition systems. In this paper, we contribute a new million-scale recognition …

We propose a discrimination-aware learning method to improve both the accuracy and
fairness of biased face recognition algorithms. The most popular face recognition …