Human Action Recognition (HAR) aims to understand human behavior and assign a label to
each action. It has a wide range of applications, and therefore has been attracting increasing …

Skeleton-based action recognition has rapidly become one of the most popular and
essential research topics in computer vision. The task is to analyze the characteristics of …

Recent transformer-based solutions have been introduced to estimate 3D human pose from
2D keypoint sequence by considering body joints among all frames globally to learn spatio …

Human activity recognition (HAR) plays a pivotal role in various domains, including
healthcare, sports, robotics, and security. With the growing popularity of wearable devices …

The COVID-19 pandemic has sped up the acceptance of online education as a substitute for
conventional classroom instruction. E-Learning emerged as an instant solution to avoid …

In recent years, graph convolutional networks (GCNs) play an increasingly critical role in
skeleton-based human action recognition. However, most GCN-based methods still have …

Extracting effective spatial-temporal information is significantly important for video-based
action recognition. Recently 3D convolutional neural networks (3D CNNs) that could …

Vehicle detection and classification are the most significant and challenging activities of an
intelligent traffic monitoring system. Traditional methods are highly computationally …

Skeleton-based human action recognition has attracted increasing attention and many
methods have been proposed to boost the performance. However, these methods still …

With the rapid growth of multimedia technologies, many images are communicated over
public channels. Therefore, significant interest has been given to providing secure …