A two-stage temporal proposal network for precise action localization in untrimmed video
Author:
Publisher
Springer Science and Business Media LLC
Subject
Artificial Intelligence,Computer Vision and Pattern Recognition,Software
Link
https://link.springer.com/content/pdf/10.1007/s13042-021-01301-z.pdf
Reference66 articles.
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2. Tu Z, Xie W, Dauwels J, Li B, Yuan J (2019) Semantic cues enhanced multimodality multistream CNN for action recognition. IEEE Trans Circuits Syst Video Technol 29(5):1423–1437
3. Liu K, Gao L, Khan NM, Qi L, Guan L (2020) A multi-stream graph convolutional networks-hidden conditional random field model for skeleton-based action recognition. In: IEEE Transactions on Multimedia, vol 23, 2021, pp 64–76. https://doi.org/10.1109/TMM.2020.2974323
4. Lee I, Kim D, Lee S (2020) 3D human behavior understanding using generalized TS-LSTM networks. In: IEEE Transactions on Multimedia, vol 23, 2021, pp415–428. https://doi.org/10.1109/TMM.2020.2978637
5. Yang J, Liu W, Yuan J, Mei T (2020) Hierarchical soft quantization for skeleton-based human action recognition. In: IEEE Transactions on Multimedia, vol 23, 2021, pp 883–898. https://doi.org/10.1109/TMM.2020.2990082
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