Self-Relational Graph Convolution Network for Skeleton-Based Action Recognition-Reference-Cited by-同舟云学术

Self-Relational Graph Convolution Network for Skeleton-Based Action Recognition

Published:2023-10-26 Issue: Volume: Page:
ISSN:
Container-title:Proceedings of the 31st ACM International Conference on Multimedia
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Author:

Yussif Sophyani Banaamwini¹^ORCID,Xie Ning¹^ORCID,Yang Yang¹^ORCID,Shen Heng Tao¹^ORCID

Affiliation:

1. University of Electronic Science and Technology of China, Chengdu, China

Funder

National Key R&D Program of China

Chengdu Science and Technology Project

National Natural Science Foundation of China

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3581783.3612280

Reference49 articles.

1. Sami Abu-El-Haija , Bryan Perozzi , Amol Kapoor , Nazanin Alipourfard , Kristina Lerman , Hrayr Harutyunyan , Greg Ver Steeg , and Aram Galstyan . 2019 . Mixhop: Higher-order graph convolutional architectures via sparsified neighborhood mixing . In International Conference on Machine Learning. 21--29 . Sami Abu-El-Haija, Bryan Perozzi, Amol Kapoor, Nazanin Alipourfard, Kristina Lerman, Hrayr Harutyunyan, Greg Ver Steeg, and Aram Galstyan. 2019. Mixhop: Higher-order graph convolutional architectures via sparsified neighborhood mixing. In International Conference on Machine Learning. 21--29.

2. Channel-wise Topology Refinement Graph Convolution for Skeleton-Based Action Recognition

3. Decoupling GCN with DropGraph Module for Skeleton-Based Action Recognition

4. Skeleton-Based Action Recognition With Shift Graph Convolutional Network

5. Extremely Lightweight Skeleton-Based Action Recognition With ShiftGCN++

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