Automated surveillance systems observe the environment utilizing cameras. The observed
scenario is then analysed using motion detection, crowd behaviour, individual behaviour …

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 …

In real-world scenarios, many factors may harm face recognition performance, eg., large
pose, bad illumination, low resolution, blur and noise. To address these challenges …

In this work, a face recognition method is proposed for face under pose variations using a
multitask convolutional neural network (CNN). Furthermore, a pose estimation method …

Abstract 3D face reconstruction is the most captivating topic in biometrics with the advent of
deep learning and readily available graphical processing units. This paper explores the …

Learning-based face reconstruction methods have recently shown promising performance in
recovering face geometry from a single image. However, the lack of training data with 3D …

Deep learning based facial landmark detection (FLD) has made rapid progress. However,
the accuracy and robustness of FLD algorithms are degraded heavily when the face is …

Computer vision systems open a new challenge to recognize human faces under varied
poses in similar capacity and capability as human-beings perform naturally. For surveillance …

In this work, a new multitask convolutional neural network (CNN) is proposed aiming for the
recognition of face under pose variations. Furthermore, the combination of pose estimation …

Restoration of a 3D face from the mesh image is highly demanded in computer vision
applications. 3D face restoration is a challenging task due to the variation of expression …