Multi-scale spatial–temporal convolutional neural network for skeleton-based action recognition
Author:
Publisher
Springer Science and Business Media LLC
Subject
Artificial Intelligence,Computer Vision and Pattern Recognition
Link
https://link.springer.com/content/pdf/10.1007/s10044-023-01156-w.pdf
Reference58 articles.
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2. Li M, Chen S, Chen X, Zhang Y, Wang Y, Tian Q (2019) Actional-structural graph convolutional networks for skeleton-based action recognition. In: IEEE/CVF conference on computer vision and pattern recognition (CVPR), pp. 3590–3598 . https://doi.org/10.1109/CVPR.2019.00371
3. Liu J, Shahroudy A, Xu D, Wang G (2016) Spatio-temporal lstm with trust gates for 3d human action recognition. In: European conference on computer vision (ECCV), pp. 816–833. Springer, Cham
4. Shi L, Zhang Y, Cheng J, Lu H (2019) Skeleton-based action recognition with directed graph neural networks. In: IEEE/CVF conference on computer vision and pattern recognition (CVPR), pp. 7904–7913.https://doi.org/10.1109/CVPR.2019.00810
5. Shi L, Zhang Y, Cheng J, Lu H (2019)Two-stream adaptive graph convolutional networks for skeleton-based action recognition. In: IEEE/CVF conference on computer vision and pattern recognition (CVPR), pp. 12018–12027. https://doi.org/10.1109/CVPR.2019.01230
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