Structure and Sequencing Preserving Representations for Skeleton-based Action Recognition Relying on Attention Mechanisms
Author:
Publisher
Springer Science and Business Media LLC
Subject
Hardware and Architecture,Modeling and Simulation,Information Systems,Signal Processing,Theoretical Computer Science,Control and Systems Engineering
Link
https://link.springer.com/content/pdf/10.1007/s11265-023-01892-6.pdf
Reference51 articles.
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2. Pareek, P., & Thakkar, A. (2021). A survey on video-based human action recognition: recent updates, datasets, challenges, and applications. Artificial Intelligence Review, 54, 2259–2322.
3. Li, M., Leung, H., & Shum, H. P. (2016). Human action recognition via skeletal and depth based feature fusion. In Proceedings of the 9th International Conference on Motion in Games (pp. 123-132).
4. Khan, M. A., Javed, K., Khan, S. A., Saba, T., Habib, U., Khan, J. A., & Abbasi, A. A. (2020). Human action recognition using fusion of multiview and deep features: an application to video surveillance. Multimedia Tools and Applications, 1-27.
5. Wang, H., & Schmid, C. (2013). Action recognition with improved trajectories. In Proceedings of the IEEE International Conference on Computer Vision (pp. 3551-3558).
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