Affective computing conjoins the research topics of emotion recognition and sentiment
analysis, and can be realized with unimodal or multimodal data, consisting primarily of …

Recently, generative adversarial networks (GANs) have progressed enormously, which
makes them able to learn complex data distributions in particular faces. More and more …

Facial expression recognition (FER) in the wild received broad concerns in which occlusion
and pose variation are two key issues. This paper proposed a global multi-scale and local …

Though tremendous strides have been made in uncontrolled face detection, accurate and
efficient 2D face alignment and 3D face reconstruction in-the-wild remain an open …

Though tremendous strides have been made in uncontrolled face detection, accurate and
efficient face localisation in the wild remains an open challenge. This paper presents a …

Facial Expression Recognition (FER) in the wild is extremely challenging due to occlusions,
variant head poses, face deformation and motion blur under unconstrained conditions …

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 …

In this paper, we propose a novel Feature Decomposition and Reconstruction Learning
(FDRL) method for effective facial expression recognition. We view the expression …

This paper proposes a method for head pose estimation from a single image. Previous
methods often predict head poses through landmark or depth estimation and would require …

Micro-expressions (MEs) are important clues for reflecting the real feelings of humans, and
micro-expression recognition (MER) can thus be applied in various real-world applications …