Low-resolution face recognition (LRFR) is an active research area as it is widely used in
forensics and surveillance systems. A lot of effort has been put into improving the …

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 …

Recent years witnessed the breakthrough of face recognition with deep convolutional neural
networks. Dozens of papers in the field of FR are published every year. Some of them were …

Face recognition from side‐view positions poses a considerable challenge in automatic face
recognition tasks. Pose variation up to the side‐view is an issue of difference in appearance …

Overcoming image acquisition perspectives and face pose variations is a key problem in
unconstrained face recognition tasks. One of the practical approaches is by reconstructing …

Recent studies have highlighted a major caveat in several popular deep learning based
face recognition algorithms. Despite their high accuracy, they have shown to exhibit biased …

Even though numerous studies have been conducted, face recognition still suffers from poor
performance in pose variance. Besides fine appearance details of the face from RGB …

A method including generating a captured facial object and a captured pose from a captured
image. The method also includes obtaining a base facial object and a base pose from a …