Topology-learnable graph convolution for skeleton-based action recognition

Guangming Zhu; Liang Zhang; Hongsheng Li; Peiyi Shen; Syed Afaq Ali Shah; Mohammed Bennamoun

doi:10.1016/j.patrec.2020.05.005

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Topology-learnable graph convolution for skeleton-based action recognition

Guangming Zhu Liang Zhang Hongsheng Li Peiyi Shen Syed Afaq Ali Shah Mohammed Bennamoun

Year: 2020 Journal: Pattern Recognition Letters Vol: 135 Pages: 286-292 Publisher: Elsevier BV

DOI: 10.1016/j.patrec.2020.05.005

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Keywords:

Adjacency matrix Computer science Topological graph theory Topology (electrical circuits) Graph Voltage graph Action recognition Initialization Null graph Artificial intelligence Pattern recognition (psychology) Theoretical computer science Line graph Mathematics Combinatorics

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Human Pose and Action Recognition

Physical Sciences → Computer Science → Computer Vision and Pattern Recognition

Hand Gesture Recognition Systems

Physical Sciences → Computer Science → Human-Computer Interaction

Gait Recognition and Analysis

Physical Sciences → Engineering → Biomedical Engineering

Topology-learnable graph convolution for skeleton-based action recognition

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