3D human action representation and recognition are important issues in many multimedia
applications. While latent state approaches have been widely used for action modeling …

Human action recognition is an important yet challenging task. Human actions usually
involve human-object interactions, highly articulated motions, high intra-class variations, and …

Recently, skeleton-based action recognition has become increasingly prevalent in computer
vision due to its wide range of applications, and many approaches have been proposed to …

3D human action recognition has received increasing attention due to its potential
application in video surveillance equipment. To guarantee satisfactory performance …

For 3D action recognition, the main challenge is to extract long-range semantic information
in both temporal and spatial dimensions. In this paper, in order to better excavate long-range …

Recently, human activity recognition using skeleton data is increasing due to its ease of
acquisition and finer shape details. Still, it suffers from a wide range of intra-class variation …

In this paper, we proposed multi-perspective and multi-modality discriminated and joint
representation and recognition model for 3D action recognition. Specifically, for depth and …

Abstract 3D action recognition–analysis of human actions based on 3D skeleton data–
becomes popular recently due to its succinctness, robustness, and view-invariant …

Graph convolutional networks have achieved remarkable performance in action recognition
from skeleton videos. However, most of the existing GCN-based methods improve …

As the prosperity of low-cost and easy-operating depth cameras, skeleton-based human
action recognition has been extensively studied recently. However, most of the existing …