Two Stream Multi-Attention Graph Convolutional Network for Skeleton-Based Action Recognition
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Publisher
Springer Nature Singapore
Link
https://link.springer.com/content/pdf/10.1007/978-981-99-9109-9_11
Reference17 articles.
1. Cao, Y., Liu, C., Huang, Z., Sheng, Y., Ju, Y.: Skeleton-based action recognition with temporal action graph and temporal adaptive graph convolution structure. Multimed. Tools Appl. 80(19), 29139–29162 (2021)
2. Cao, Z., Simon, T., Wei, S.E., Sheikh, Y.: Realtime multi-person 2D pose estimation using part affinity fields. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp. 7291–7299 (2017)
3. Chen, S., Xu, K., Jiang, X., Sun, T.: Spatiotemporal-spectral graph convolutional networks for skeleton-based action recognition. In: 2021 IEEE International Conference on Multimedia & Expo Workshops (ICMEW), pp. 1–6. IEEE (2021)
4. Duan, H., Zhao, Y., Chen, K., Lin, D., Dai, B.: Revisiting skeleton-based action recognition. In: Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, pp. 2969–2978 (2022)
5. Fu, Y., et al.: Partial feature selection and alignment for multi-source domain adaptation. In: Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, pp. 16654–16663 (2021)
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