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 …

The visual recognition and understanding of human actions remain an active research
domain of computer vision, being the scope of various research works over the last two …

Skeleton-based generative modelling is an important research topic to mitigate the heavy
annotation process. In this work, we explore the impact of synthetic data on skeleton-based …

Self-supervised learning (SSL) is a promising method for gaining perception and common
sense from unlabelled data. Existing approaches to analyzing human body skeletons …

Graph convolution networks (GCNs) have been widely used in the field of skeleton-based
human action recognition. However, it is still difficult to improve recognition performance and …

Skeleton-based action recognition is a crucial but challenging task in the application of
engineering algorithms. However, due to the inaccurate estimation quality, certain joints that …

Continuous Hand Gesture Recognition (CHGR) has been extensively studied by
researchers in the last few decades. Recently, one model has been presented to deal with …

The total organic carbon (TOC) is a key geologic parameter for unconventional reservoirs.
Conventional empirical Δ Log R methods cannot handle the nonlinear relationships …

Action recognition plays a pivotal role in understanding and interpreting human behavior
within videos, finding applications across various domains such as surveillance, human …