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Title: A Survey on Skeleton-Based Activity Recognition using Graph Convolutional Networks (GCN)
Skeleton-Based Activity recognition is an active research topic in Computer Vision. In recent years, deep learning methods have been used in this area, including Recurrent Neural Network (RNN)-based, Convolutional Neural Network (CNN)-based and Graph Convolutional Network (GCN)-based approaches. This paper provides a survey of recent work on various Graph Convolutional Network (GCN)-based approaches being applied to Skeleton-Based Activity Recognition. We first introduce the conventional implementation of a GCN. Then methods that address the limitations of conventional GCN's are presented.  more » « less
Award ID(s):
1831969
NSF-PAR ID:
10356217
Author(s) / Creator(s):
; ; ; ;
Date Published:
Journal Name:
The 12th Int’l Symposium on Image and Signal Processing and Analysis (ISPA)
Page Range / eLocation ID:
177 to 182
Format(s):
Medium: X
Sponsoring Org:
National Science Foundation
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