With the advances of data-driven machine learning research, a wide variety of prediction
problems have been tackled. It has become critical to explore how machine learning and …

Affective computing has an unprecedented potential to change the way humans interact with
technology. While the last decades have witnessed vast progress in the field, multimodal …

As various databases of facial expressions have been made accessible over the last few
decades, the Facial Expression Recognition (FER) task has gotten a lot of interest. The …

Facial expression recognition (FER) is of great interest to the current studies of human-
computer interaction. In this paper, we propose a novel geometry-guided facial expression …

Graph is powerful for representing various types of real-world data. The topology (edges'
presence) and edges' features of a graph decides the message passing mechanism among …

Learning discriminative representations with good robustness from facial observations
serves as a fundamental step towards intelligent facial expression recognition (FER). In this …

Deep convolutional neural networks (CNNs) have become the standard model architecture
for facial expression recognition (FER). However, CNN-based models struggle to capture …

Facial expression recognition (FER) is a crucial task for human emotion analysis and has
attracted wide interest in the field of computer vision and affective computing. General …

Video-based automatic depression analysis provides a fast, objective and repeatable self-
assessment solution, which has been widely developed in recent years. While depression …

As one of the most important affective signals, facial affect analysis (FAA) is essential for
developing human-computer interaction systems. Early methods focus on extracting …