5 citations · 8 across the 4 of their papers we have counts for
4 papers
KAN-HyperpointNet for Point Cloud Sequence-Based 3D Human Action Recognition
Zhaoyu Chen, Xing Li, Qian Huang +3
Point cloud sequence-based 3D action recognition has achieved impressive performance and efficiency. However, existing point cloud sequence modeling methods cannot adequately balan…
DD-GCN: Directed Diffusion Graph Convolutional Network for Skeleton-based Human Action Recognition
Chang Li, Qian Huang, Yingchi Mao
Graph Convolutional Networks (GCNs) have been widely used in skeleton-based human action recognition. In GCN-based methods, the spatio-temporal graph is fundamental for capturing m…
Real-time 3D human action recognition based on Hyperpoint sequence
Xing Li, Qian Huang, Zhijian Wang +3
Real-time 3D human action recognition has broad industrial applications, such as surveillance, human-computer interaction, and healthcare monitoring. By relying on complex spatio-t…
Human Action Recognition Based on Multi-scale Feature Maps from Depth Video Sequences
Chang Li, Qian Huang, Xing Li +1
Human action recognition is an active research area in computer vision. Although great process has been made, previous methods mostly recognize actions based on depth data at only…