Cmf-transformer: cross-modal fusion transformer for human action recognition
Author:
Funder
National Natural Science Foundation of China
Science and Technology Project of Hunan
Publisher
Springer Science and Business Media LLC
Link
https://link.springer.com/content/pdf/10.1007/s00138-024-01598-0.pdf
Reference54 articles.
1. Elharrouss, O., Almaadeed, N., Al-Maadeed, S.A., Bouridane, A., Beghdadi, A.: A combined multiple action recognition and summarization for surveillance video sequences. Appl. Intell. 51, 690–712 (2020)
2. Baradel, F., Wolf, C., Mille, J., Taylor, G.W.: Glimpse clouds: Human activity recognition from unstructured feature points. In: 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition, pp. 469–478 (2018). https://doi.org/10.1109/CVPR.2018.00056
3. Wang, Z., She, Q., Smolic, A.: Action-net: Multipath excitation for action recognition. In: 2021 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), pp. 13209–13218 (2021). https://doi.org/10.1109/CVPR46437.2021.01301
4. Liu, X., Pintea, S.L., Nejadasl, F.K., Booij, O., van Gemert, J.C.: No frame left behind: Full video action recognition. In: 2021 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), pp. 14887–14896 (2021). https://doi.org/10.1109/CVPR46437.2021.01465
5. Mazzia, V., Angarano, S., Salvetti, F., Angelini, F., Chiaberge, M.: Action transformer: a self-attention model for short-time pose-based human action recognition. Pattern Recogn. 124, 108487 (2022). https://doi.org/10.1016/j.patcog.2021.108487
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