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 …

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 …

Face image quality assessment (FIQA) estimates the utility of the captured image in
achieving reliable and accurate recognition performance. This work proposes a novel FIQA …

Abstract In recent years, Face Image Quality Assessment (FIQA) has become an
indispensable part of the face recognition system to guarantee the stability and reliability of …

Since December 2019, the COVID-19 pandemic has led to a dramatic loss of human lives
and caused severe economic crises worldwide. COVID-19 virus transmission generally …

Modern face recognition (FR) models excel in constrained scenarios, but often suffer from
decreased performance when deployed in unconstrained (real-world) environments due to …

Can deep learning models achieve greater generalization if their training is guided by
reference to human perceptual abilities? And how can we implement this in a practical …

Quality scores provide a measure to evaluate the utility of biometric samples for biometric
recognition. Biometric recognition systems require high-quality samples to achieve optimal …

Existing face restoration models have relied on general assessment metrics that do not
consider the characteristics of facial regions. Recent works have therefore assessed their …

End-to-end face quality assessment based on deep learning can directly predict the overall
quantitative score of face quality, thus hel** to control the risk of face recognition system …