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 …

Human action recognition systems use data collected from a wide range of sensors to
accurately identify and interpret human actions. One of the most challenging issues for …

Human skeleton-based action recognition offers a valuable means to understand the
intricacies of human behavior because it can handle the complex relationships between …

Research on depth-based human activity analysis achieved outstanding performance and
demonstrated the effectiveness of 3D representation for action recognition. The existing …

Sign language is commonly used by deaf or speech impaired people to communicate but
requires significant effort to master. Sign Language Recognition (SLR) aims to bridge the …

Abstract Skeleton-based Human Activity Recognition has achieved great interest in recent
years as skeleton data has demonstrated being robust to illumination changes, body scales …

Skeleton-based action recognition is an important task that requires the adequate
understanding of movement characteristics of a human action from the given skeleton …

Recent years have witnessed the success of deep learning methods in human activity
recognition (HAR). The longstanding shortage of labeled activity data inherently calls for a …

In 3D human action recognition, limited supervised data makes it challenging to fully tap into
the modeling potential of powerful networks such as transformers. As a result, researchers …

In this paper, we propose a deep progressive reinforcement learning (DPRL) method for
action recognition in skeleton-based videos, which aims to distil the most informative frames …