Lin, Wei
Zeng, Huanqiang http://orcid.org/0000-0002-2802-7745
Zhu, Jianqing
Hsia, Chih-Hsien
Hou, Junhui
Ma, Kai-Kuang
Funding for this research was provided by:
National Key R &D Program of China (2021YFE0205400)
National Natural Science Foundation of China (61871434, 61976098)
Natural Science Foundation for Outstanding Young Scholars of Fujian Province (2022J06023)
Natural Science Foundation of Fujian Province (2022J01294)
Collaborative Innovation Platform Project of Fuzhou-Xiamen- Quanzhou National Independent Innovation Demonstration Zone (2021FX03)
Article History
Received: 31 August 2022
Accepted: 26 November 2023
First Online: 26 December 2023
Declarations
:
: We declare that we have no financial and personal relationships with other people or organizations that can inappropriately influence our work, and there is no professional or other personal interest of any nature or kind in any product, service and/or company that could be construed as influencing the position presented in, or the review of, the manuscript entitled ‘Unsupervised Video-Based Action Recognition Using Two-Stream Generative Adversarial Network.’