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 …

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 …

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 …

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 …

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 …

This paper presents a new mechanism for improving the convergence properties of path
vector routing algorithms, such as BGP. Using a route's path information, we develop two …

In this work, we introduce the concept of pixel-level gface image quality that determines the
utility of single pixels in a face image for recognition. We propose a training-free approach to …

Abstract Face Image Quality Assessment (FIQA) is pivotal for guaranteeing the accuracy of
face recognition in unconstrained environments. Recent progress in deep quality-fitting …

Scientific fields that are interested in faces have developed their own sets of concepts and
procedures for understanding how a target model system (be it a person or algorithm) …

Knowing when an output can be trusted is critical for reliably using face recognition systems.
While there has been enormous effort in recent research on improving face verification …