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 …

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 …

Facial expression recognition is a hot research topic and can be applied in many computer
vision fields, such as human–computer interaction, affective computing and so on. In this …

Automatic facial expression recognition (FER) has gained much attention due to its
applications in human-computer interaction. Among the approaches to improve FER tasks …

Abstract Facial Expression Recognition (FER) has long been a challenging task in the field
of computer vision. In this paper, we present a novel model, named Deep Attentive Multi …

Facial expression recognition (FER) in the wild is a novel and challenging topic in the field of
human emotion perception. Different kinds of convolutional neural network (CNN) …

Facial expression recognition (FER) has long been a challenging task in computer vision. In
this paper, we propose a novel method, named deep comprehensive multipatches …

Attention based convolutional neural networks (CNNs) for facial expression recognition
(FER) apply attention that is uniform across either spatial dimensions or channel dimensions …

Facial expressions are mirrors of human thoughts and feelings. It provides a wealth of social
cues to the viewer, including the focus of attention, intention, motivation, and emotion. It is …

Deep convolutional neural networks have achieved great success in facial expression
datasets both under laboratory conditions and in the wild. However, most of these related …