Three-dimensional skeleton-based action recognition (3D SAR) has gained important
attention within the computer vision community, owing to the inherent advantages offered by …

Action recognition is a major branch of computer vision research. As a widely used
technology, action recognition has been applied to human–computer interaction, intelligent …

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 has been widely investigated considering their strong
adaptability to dynamic circumstances and complicated backgrounds. To recognize different …

Skeleton-based action recognition, which classifies human actions based on the
coordinates of joints and their connectivity within skeleton data, is widely utilized in various …

Human action recognition and posture prediction aim to recognize and predict respectively
the action and postures of persons in videos. They are both active research topics in …

Human activity recognition aims to determine actions performed by a human in an image or
video. Examples of human activity include standing, running, sitting, slee**, etc. These …

Current methods for skeleton-based human action recognition usually work with completely
observed skeletons. However, in real scenarios, it is prone to capture incomplete and noisy …

For skeleton-based action recognition, most of the existing works used recurrent neural
networks. Using convolutional neural networks (CNNs) is another attractive solution …

With the advancement of computer vision, human action recognition (HAR) has shown its
broad research worth and application prospects in a wide range of fields such as intelligent …