Emotion recognition plays a significant role in cognitive psychology research. However,
measuring emotions is a challenging task. Thus, several approaches have been designed …

Emotion recognition has opened up many challenges, which lead to various advances in
computer vision and artificial intelligence. The rapid development in this field has …

Research in automatic analysis of facial expressions mainly focuses on recognising the
seven basic ones. However, compound expressions are more diverse and represent the …

This paper presents a novel facial expression recognition network, called Distract your
Attention Network (DAN). Our method is based on two key observations in biological visual …

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 …

This paper presents an efficiently robust facial expression recognition (FER) network, named
EfficientFace, which holds much fewer parameters but more robust to the FER in the wild …

Learning discriminative features for Facial Expression Recognition (FER) in the wild using
Convolutional Neural Networks (CNNs) is a non-trivial task due to the significant intra-class …

Automated Facial Expression Recognition (FER) in the wild using deep neural networks is
still challenging due to intra-class variations and inter-class similarities in facial images …

Current artificial intelligence systems for determining a person's emotions rely heavily on lip
and mouth movement and other facial features such as eyebrows, eyes, and the forehead …

Learning discriminative features is of vital importance for automatic facial expression
recognition (FER) in the wild. In this article, we propose a novel Slide-Patch and Whole-Face …