The paper addresses the problem of pose-invariant recognition of faces via an MRF
matching model. Unlike previous costly matching approaches, the proposed algorithm …

The variation of facial appearance due to the viewpoint (/pose) degrades face recognition
systems considerably, which is well known as one of the bottlenecks in face recognition …

Face recognition across large pose changes is one of the hardest problems for automatic
face recognition. Recently, approaches that use partial least squares (PLS) to compute …

In this paper, a novel method is proposed for real-world pose-invariant face recognition from
only a single image in a gallery. A 3D Facial Expression Generic Elastic Model (3D FE-GEM) …

Pose-invariant face recognition (PIFR) refers to the ability that recognizes face images with
arbitrary pose variations. Among existing PIFR algorithms, pose normalization has been …

A pose-invariant face recognition system based on an image matching method formulated
on MRFs is presented. The method uses the energy of the established match between a pair …

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

One of the key challenges for current face recognition techniques is how to handle pose
variations between the probe and gallery face images. In this paper, we present a method …

This paper explores multi-task learning (MTL) for face recognition. First, we propose a multi-
task convolutional neural network (CNN) for face recognition, where identity classification is …

We propose a novel pose-invariant face recognition approach which we call Discriminant
Multiple Coupled Latent Subspace framework. It finds the sets of projection directions for …