arXiv Open Access 2024

Extended multi-stream temporal-attention module for skeleton-based human action recognition (HAR)

Faisal Mehmood Xin Guo Enqing Chen Muhammad Azeem Akbar Arif Ali Khan +1 lainnya

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Abstrak

Graph convolutional networks (GCNs) are an effective skeleton-based human action recognition (HAR) technique. GCNs enable the specification of CNNs to a non-Euclidean frame that is more flexible. The previous GCN-based models still have a lot of issues: (I) The graph structure is the same for all model layers and input data.

Topik & Kata Kunci

cs.CV

Penulis (6)

Faisal Mehmood

Xin Guo

Enqing Chen

Muhammad Azeem Akbar

Arif Ali Khan

Sami Ullah

Format Sitasi

APA MLA BibTeX

Mehmood, F., Guo, X., Chen, E., Akbar, M.A., Khan, A.A., Ullah, S. (2024). Extended multi-stream temporal-attention module for skeleton-based human action recognition (HAR). https://arxiv.org/abs/2411.06553

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Informasi Jurnal

Tahun Terbit: 2024
Bahasa: en
Sumber Database: arXiv
Akses: Open Access ✓