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\begin{thebibliography}{10}\itemsep=-1pt
\bibitem{cao2019openpose}
Zhe Cao, Gines Hidalgo, Tomas Simon, Shih-En Wei, and Yaser Sheikh.
\newblock Openpose: Realtime multi-person 2d pose estimation using part
affinity fields.
\newblock {\em arXiv:1812.08008}, 2019.
\bibitem{estevam2020zeroshot}
Valter Estevam, Helio Pedrini, and David Menotti.
\newblock Zero-shot action recognition in videos: A survey.
\newblock {\em arXiv:1909.06423}, 2020.
\bibitem{gupta2021syntactically}
Pranay Gupta, Divyanshu Sharma, and Ravi~Kiran Sarvadevabhatla.
\newblock Syntactically guided generative embeddings for zero-shot skeleton
action recognition.
\newblock {\em arXiv:2101.11530}, 2021.
\bibitem{jasani2019skeleton}
Bhavan Jasani and Afshaan Mazagonwalla.
\newblock Skeleton based zero shot action recognition in joint pose-language
semantic space.
\newblock {\em arXiv:1911.11344}, 2019.
\bibitem{kopuk2019realtime}
Okan Köpüklü, Ahmet Gunduz, Neslihan Kose, and Gerhard Rigoll.
\newblock Real-time hand gesture detection and classification using
convolutional neural networks.
\newblock {\em arXiv:1901.10323}, 2019.
\bibitem{Liu_2020}
Jun Liu, Amir Shahroudy, Mauricio Perez, Gang Wang, Ling-Yu Duan, and Alex~C.
Kot.
\newblock Ntu rgb+d 120: A large-scale benchmark for 3d human activity
understanding.
\newblock {\em IEEE Transactions on Pattern Analysis and Machine Intelligence},
42(10):2684–2701, Oct 2020.
\bibitem{liu2019roberta}
Yinhan Liu, Myle Ott, Naman Goyal, Jingfei Du, Mandar Joshi, Danqi Chen, Omer
Levy, Mike Lewis, Luke Zettlemoyer, and Veselin Stoyanov.
\newblock Roberta: A robustly optimized bert pretraining approach.
\newblock {\em arXiv:1907.11692}, 2019.
\bibitem{ma2019nlpaug}
Edward Ma.
\newblock Nlp augmentation.
\newblock https://github.com/makced ward/nlpaug, 2019.
\bibitem{marinov2021pose2drone}
Zdravko Marinov, Stanka Vasileva, Qing Wang, Constantin Seibold, Jiaming Zhang,
and Rainer Stiefelhagen.
\newblock Pose2drone: A skeleton-pose-based framework for human-drone
interaction.
\newblock {\em arXiv:2105.13204}, 2021.
\bibitem{Pagliardini_2018}
Matteo Pagliardini, Prakhar Gupta, and Martin Jaggi.
\newblock Unsupervised learning of sentence embeddings using compositional
n-gram features.
\newblock {\em Proceedings of the 2018 Conference of the North American Chapter
of the Association for Computational Linguistics: Human Language
Technologies, Volume 1 (Long Papers)}, 2018.
\bibitem{perez2017effectiveness}
Luis Perez and Jason Wang.
\newblock The effectiveness of data augmentation in image classification using
deep learning.
\newblock {\em arXiv:1712.04621}, 2017.
\bibitem{reimers2019sentencebert}
Nils Reimers and Iryna Gurevych.
\newblock Sentence-bert: Sentence embeddings using siamese bert-networks.
\newblock {\em arXiv:1908.10084}, 2019.
\bibitem{sung2018learning}
Flood Sung, Yongxin Yang, Li Zhang, Tao Xiang, Philip H.~S. Torr, and
Timothy~M. Hospedales.
\newblock Learning to compare: Relation network for few-shot learning.
\newblock {\em arXiv:1711.06025}, 2018.
\bibitem{yan2018spatial}
Sijie Yan, Yuanjun Xiong, and Dahua Lin.
\newblock Spatial temporal graph convolutional networks for skeleton-based
action recognition.
\newblock {\em arXiv:1801.07455}, 2018.
\end{thebibliography}
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\OT1/ptm/m/n/9 H. S. Torr, and Tim-o-thy M. Hospedales. Learn-ing
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