Face quality assessment aims at estimating the utility of a face image for the purpose of
recognition. It is a key factor to achieve high face recognition performances. Currently, the …

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 …

Face image quality is an important factor to enable high-performance face recognition
systems. Face quality assessment aims at estimating the suitability of a face image for the …

The quality of face images varies due to complex environmental factors, and face images
with extremely poor qualities would deteriorate the performance of face recognition. As one …

Face image quality assessment (FIQA) attempts to improve face recognition (FR)
performance by providing additional information about sample quality. Because FIQA …

" The output of a computerised system can only be as accurate as the information entered
into it." This rather trivial statement is the basis behind one of the driving concepts in …

In this paper we develop FaceQgen 1 1 Publicly available in: https://github. com/uam-
biometrics/FaceQgen, a No-Reference Quality Assessment approach for face images based …

In this paper we develop a Quality Assessment approach for face recognition based on deep
learning. The method consists of a Convolutional Neural Network, FaceQnet, that is used to …

Face image quality can be defined as a measure of the utility of a face image to automatic
face recognition. In this paper, we propose (and compare) two methods for learning face …

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