FP-GCN: A Novel Feature Pyramid Graph Convolutional Network For Skeleton-based Action Recognition

Chengyuan Ke; Sheng Liu; Zhenghao Ke; Yuan Feng

doi:10.1109/smc54092.2024.10831239

ScienceGate Book Chapters

JOURNAL ARTICLE

FP-GCN: A Novel Feature Pyramid Graph Convolutional Network For Skeleton-based Action Recognition

Chengyuan Ke Sheng Liu Zhenghao Ke Yuan Feng

Year: 2024 Pages: 3715-3720

DOI: 10.1109/smc54092.2024.10831239

Get Full-Text PDF Get Analytical Report

Keywords:

Skeleton (computer programming) Computer science Pattern recognition (psychology) Pyramid (geometry) Artificial intelligence Feature (linguistics) Graph Action recognition Feature extraction Convolutional neural network Mathematics Theoretical computer science Geometry

Metrics

Cited By

0.53

FWCI (Field Weighted Citation Impact)

Refs

0.62

Citation Normalized Percentile

Is in top 1%

Is in top 10%

Citation History

Topics

Human Pose and Action Recognition

Physical Sciences → Computer Science → Computer Vision and Pattern Recognition

Anomaly Detection Techniques and Applications

Physical Sciences → Computer Science → Artificial Intelligence

Gait Recognition and Analysis

Physical Sciences → Engineering → Biomedical Engineering

FP-GCN: A Novel Feature Pyramid Graph Convolutional Network For Skeleton-based Action Recognition

Metrics

Citation History

Topics

Related Documents

LSTF-GCN: local spatio-temporal feature fusion graph convolutional network for skeleton-based action recognition

TFC-GCN: Lightweight Temporal Feature Cross-Extraction Graph Convolutional Network for Skeleton-Based Action Recognition

FD-GCN: Feedback Directed Graph Convolutional Network for skeleton-based action recognition

DA-GCN: Deformable Adaptive - Graph Convolutional Network for Skeleton-Based Action Recognition

Feature reconstruction graph convolutional network for skeleton-based action recognition