Affective computing is one of the most important research fields in modern human–computer
interaction (HCI). The goal of affective computing is to study and develop the theories …

Facial emotion recognition (FER) is a computer vision process aimed at detecting and
classifying human emotional expressions. FER systems are currently used in a vast range of …

In this article, behaviour of students in the e-learning environment is analyzed. The novel
pipeline is proposed based on video facial processing. At first, face detection, tracking and …

Micro-action is an imperceptible non-verbal behaviour characterised by low-intensity
movement. It offers insights into the feelings and intentions of individuals and is important for …

Due to the subjective annotation and the inherent inter-class similarity of facial expressions,
one of key challenges in Facial Expression Recognition (FER) is the annotation ambiguity …

Although significant progress has been made to audio-driven talking face generation,
existing methods either neglect facial emotion or cannot be applied to arbitrary subjects. In …

Audio-driven talking-head synthesis is a popular research topic for virtual human-related
applications. However, the inflexibility and inefficiency of existing methods, which …

Occlusion and pose variations, which can change facial appearance significantly, are two
major obstacles for automatic Facial Expression Recognition (FER). Though automatic FER …

Current benchmarks for facial expression recognition (FER) mainly focus on static images,
while there are limited datasets for FER in videos. It is still ambiguous to evaluate whether …

In this paper, the multi-task learning of lightweight convolutional neural networks is studied
for face identification and classification of facial attributes (age, gender, ethnicity) trained on …