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 …

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

This work focuses on the task of elderly activity recognition, which is a challenging task due
to the existence of individual actions and human-object interactions in elderly activities …

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

The characteristics of the complex background in crop disease image, the small disease
area, and the small contrast between the disease region and the background that easily …

Skeleton-based human action recognition is becoming increasingly important in a variety of
fields. Most existing works train a CNN or GCN based backbone to extract spatial-temporal …

In the task of skeleton-based action recognition, long-term temporal dependencies are
significant cues for sequential skeleton data. State-of-the-art methods rarely have access to …

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 …

Benefited from the powerful ability of spatial temporal Graph Convolutional Networks (ST-
GCNs), skeleton-based human action recognition has gained promising success. However …

With the fast development of effective and low-cost human skeleton capture systems,
skeleton-based action recognition has attracted much attention recently. Most existing …