In recent years, researchers have proposed many deep learning (DL) methods for various
tasks, and particularly face recognition (FR) made an enormous leap using these …

Human faces in surveillance videos often suffer from severe image blur, dramatic pose
variations, and occlusion. In this paper, we propose a comprehensive framework based on …

Occlusion poses a major challenge for person re-identification (ReID). Existing approaches
typically rely on outside tools to infer visible body parts, which may be suboptimal in terms of …

In this paper, we propose a simultaneous feature and dictionary learning (SFDL) method for
image set-based face recognition, where each training and testing example contains a set of …

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 …

In this paper we present the results of the Unconstrained Ear Recognition Challenge
(UERC), a group benchmarking effort centered around the problem of person recognition …

Abundance and availability of video capture devices, such as mobile phones and
surveillance cameras, have instigated research in video face recognition, which is highly …

In this paper, we propose a novel face synthesis approach that can generate an arbitrarily
large number of synthetic images of both real and synthetic identities. Thus a face image …

Face recognition performance has improved remarkably in the last decade. Much of this
success can be attributed to the development of deep learning techniques such as …

This paper proposes a new two-dimensional manifold learning algorithm called two-
dimensional joint local/nonlocal discriminant analysis (2DJLNDA) for 2D image feature …