Facial Expression Recognition (FER) is presently the aspect of cognitive and affective
computing with the most attention and popularity, aided by its vast application areas. Several …

Abstract Low Rank Regularization (LRR), in essence, involves introducing a low rank or
approximately low rank assumption to target we aim to learn, which has achieved great …

Face images from different perspectives reduce the accuracy of face recognition, and the
generation of frontal face images is an important research topic in the field of face …

The last few years have witnessed the great success of non-linear generative models in
synthesizing high-quality photorealistic face images. Many recent 3D facial texture …

Visual animal biometrics is an emerging research discipline in computer vision, pattern
recognition and cognitive science. It is a promising research field that encourages new …

Deep generative models learned through adversarial training have become increasingly
popular for their ability to generate naturalistic image textures. However, aside from their …

This paper presents a new approach for face and kinship verification under unconstrained
environments. The proposed approach is based on high order tensor representation of face …

Low-latency and low-power implementations of Convolutional Neural Network (CNN) are
highly desired for budget-restricted scenarios. Pruning and Winograd algorithm are two …

Face images acquired by video surveillance cameras usually involve large pose variations
which significantly degrade the performance of face recognition systems. Existing …

Discovering the common (joint) and individual subspaces is crucial for analysis of multiple
data sets, including multi-view and multi-modal data. Several statistical machine learning …