Author:
Chen Yuanzhou,Cai Shaobo,Wang Yuxin,Yan Junchi
Publisher
Springer International Publishing
Reference20 articles.
1. Liu, J.Q., Fu, P., Li, T.: On the principle of tennis “hawk-eye” system. Radio TV Broadcast Eng. 19(10), 69–73 (2012)
2. Voeikov, R., Falaleev, N., Baikulov, R.: TTNet: real-time temporal and spatial video analysis of table tennis. In: IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW), IEEE, pp. 3866–3874 (2020)
3. Dung, N.M.: 2020. maudzung/TTNet-Real-time-Analysis-System-for-Table-Tennis-Pytorch. https://github.com/maudzung/TTNet-Real-time-Analysis-System-for-Table-Tennis-Pytorch (2021)
4. Myint, H., Wong, P., Dooley, L., Hopgood, A.: Tracking a table tennis ball for umpiring purposes. In: Fourteenth IAPR International Conference on Machine Vision Applications (MVA2015), IEEE, pp. 170–173 (2015)
5. Komorowski, J., Kurzejamski, G., Sarwas, G.: Deepball: deep neural-network ball detector. In: CoRR, pp. 297–304 (2019)
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