VRGestures: Controller and Hand Gesture Datasets for Virtual Reality
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Publisher
Springer Nature Switzerland
Link
https://link.springer.com/content/pdf/10.1007/978-3-031-50075-6_26
Reference32 articles.
1. Arendttorp, E.M.N., Rodil, K., Winschiers-Theophilus, H., Magoath, C.: Overcoming legacy bias: re-designing gesture interactions in virtual reality with a san community in Namibia. In: Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, CHI 2022. Association for Computing Machinery, New York (2022)
2. Bhaumik, G., Verma, M., Govil, M.C., Vipparthi, S.K.: HyFiNet: hybrid feature attention network for hand gesture recognition. Multimedia Tools Appl. 82(4), 4863–4882 (2023)
3. D’Eusanio, A., Simoni, A., Pini, S., Borghi, G., Vezzani, R., Cucchiara, R.: A transformer-based network for dynamic hand gesture recognition. In: 2020 International Conference on 3D Vision (3DV), pp. 623–632 (2020). https://doi.org/10.1109/3DV50981.2020.00072
4. Fronteddu, G., Porcu, S., Floris, A., Atzori, L.: A dynamic hand gesture recognition dataset for human-computer interfaces. Comput. Netw. 205, 108781 (2022)
5. Gnanapriya, S., Rahimunnisa, K.: A hybrid deep learning model for real time hand gestures recognition. Intell. Autom. Soft Comput. 36(1) (2023)
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