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Graph Convolutional Neural Network for Human Action Recognition: A Comprehensive Survey

  • Published:2021-04 Issue:2 Volume:2 Page:128-145
  • ISSN:2691-4581
  • Container-title:IEEE Transactions on Artificial Intelligence
  • language:
  • Short-container-title:IEEE Trans. Artif. Intell.

Author:

Ahmad TasweerORCID,Jin LianwenORCID,Zhang XinORCID,Lai SongxuanORCID,Tang Guozhi,Lin Luojun

Funder

National Natural Science Foundation of China

Natural Science Foundation of Guangdong Province

Fundamental Research Funds for the Central Universities

Science and Technology Program of Guangzhou

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Cited by 34 articles. 订阅此论文施引文献 订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Online human motion analysis in industrial context: A review;Engineering Applications of Artificial Intelligence;2024-05

2. 3D Skeleton-Based Human Motion Prediction Using Dynamic Multi-Scale Spatiotemporal Graph Recurrent Neural Networks;IEEE Transactions on Emerging Topics in Computational Intelligence;2024-02

3. Action recognition in compressed domains: A survey;Neurocomputing;2024-02

4. Multivariate Time-Series Representation Learning via Hierarchical Correlation Pooling Boosted Graph Neural Network;IEEE Transactions on Artificial Intelligence;2024-01

5. FPGA-QHAR: Throughput-Optimized for Quantized Two-Stream Human Action Recognition on the Edge;2023 IEEE 20th International Conference on Smart Communities: Improving Quality of Life using AI, Robotics and IoT (HONET);2023-12-04
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