Deep generative models have become an emerging topic in various research areas like
computer vision and signal processing. These models allow synthesizing realistic data …

Human emotion synthesis is a crucial aspect of affective computing. It involves using
computational methods to mimic and convey human emotions through various modalities …

Capsule neural network is a new and popular technique in deep learning. However, the
traditional capsule neural network does not extract features sufficiently before the dynamic …

The scarcity of labelled data is a serious problem since deep models generally require a
large amount of training data to achieve desired performance. Data augmentation is widely …

Lack of sufficient and balanced data is one of the major challenges in hyperspectral image
classification. This problem can cause poor classification performance, especially in …

This paper proposes a data-driven approach for generating personalized smile style images
for neutral expressions, which aims to produce diverse smile styles while preserving …

Facial expressions contain a great deal of information in inter-personal communication and
social interaction and have a great impact on face recognition. This paper investigates …

This study proposes a new learning-based smile synthesis system, in which a given neutral
facial image is automatically transferred as a smile result in a certain style. Although the …

Facial expression transfer is an important problem in the computer vision community due to
its applicability in human-computer interaction, facial animation, etc. Most of the existing …

Facial expressions are an important means of communication among human beings, as they
convey different meanings in a variety of contexts. All human facial expressions, whether …