In the Internet-of-Things (IoT) era, billions of sensors and devices collect and process data
from the environment, transmit them to cloud centers, and receive feedback via the Internet …

With the transition of facial expression recognition (FER) from laboratory-controlled to
challenging in-the-wild conditions and the recent success of deep learning techniques in …

Existing public face image datasets are strongly biased toward Caucasian faces, and other
races (eg, Latino) are significantly underrepresented. The models trained from such datasets …

High-resolution representations are essential for position-sensitive vision problems, such as
human pose estimation, semantic segmentation, and object detection. Existing state-of-the …

High-resolution representation learning plays an essential role in many vision problems, eg,
pose estimation and semantic segmentation. The high-resolution network (HRNet)~\cite …

Deep learning, in particular the deep convolutional neural networks, has received
increasing interests in face recognition recently, and a number of deep learning methods …

Automated affective computing in the wild setting is a challenging problem in computer
vision. Existing annotated databases of facial expressions in the wild are small and mostly …

We present a novel boundary-aware face alignment algorithm by utilising boundary lines as
the geometric structure of a human face to help facial landmark localisation. Unlike the …

Biometric systems have the goal of measuring and analyzing the unique physical or
behavioral characteristics of an individual. The main feature of biometric systems is the use …

The locations of the fiducial facial landmark points around facial components and facial
contour capture the rigid and non-rigid facial deformations due to head movements and …