Automatic Face Recognition (FR) presents a challenging task in the field of pattern
recognition and despite the huge research in the past several decades; it still remains an …

We have collected a new face data set that will facilitate research in the problem of frontal to
profile face verificationin the wild'. The aim of this data set is to isolate the factor of pose …

In the past few years, deep learning-based models have been very successful in achieving
state-of-the-art results in many tasks in computer vision, speech recognition, and natural …

The key challenge of face recognition is to develop effective feature representations for
reducing intra-personal variations while enlarging inter-personal differences. In this paper …

Abstract In 2007, Labeled Faces in the Wild was released in an effort to spur research in
face recognition, specifically for the problem of face verification with unconstrained images …

Pose and expression normalization is a crucial step to recover the canonical view of faces
under arbitrary conditions, so as to improve the face recognition performance. An ideal …

Abstract" Frontalization" is the process of synthesizing frontal facing views of faces
appearing in single unconstrained photos. Recent reports have suggested that this process …

In this paper, we first offer an overview of advances in the field of distance metric learning.
Then, we empirically compare selected methods using a common experimental protocol …

Binary feature descriptors such as local binary patterns (LBP) and its variations have been
widely used in many face recognition systems due to their excellent robustness and strong …

This paper presents a new discriminative deep metric learning (DDML) method for face and
kinship verification in wild conditions. While metric learning has achieved reasonably good …