The capacity to recognize faces under varied poses is a fundamental human ability that
presents a unique challenge for computer vision systems. Compared to frontal face …

Abstract 3D face recognition (3DFR) has emerged as an effective means of characterizing
facial identity over the past several decades. Depending on the types of techniques used in …

Face alignment, which fits a face model to an image and extracts the semantic meanings of
facial pixels, has been an important topic in the computer vision community. However, most …

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 …

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 …

We propose a method to push the frontiers of unconstrained face recognition in the wild,
focusing on the problem of extreme pose variations. As opposed to current techniques which …

Face images captured in unconstrained environments usually contain significant pose
variation, which dramatically degrades the performance of algorithms designed to recognize …

Identifying subjects with variations caused by poses is one of the most challenging tasks in
face recognition, since the difference in appearances caused by poses may be even larger …

Face recognition has received significant attention because of its numerous applications in
access control, law enforcement, security, surveillance, Internet communication and …

Abstract 3D face recognition has become a trending research direction in both industry and
academia. It inherits advantages from traditional 2D face recognition, such as the natural …