Comparative Analysis of Fine-Tuning I3D and SlowFast Networks for Action Recognition in Surveillance Videos-Reference-Cited by-同舟云学术

Comparative Analysis of Fine-Tuning I3D and SlowFast Networks for Action Recognition in Surveillance Videos

Published:2024-01-22 Issue: Volume:5 Page:203
ISSN:
Container-title:RAiSE-2023
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Author:

Gopalakrishnan T.¹,Wason Naynika²,Krishna Raguru Jaya³,B Vamshi Krishna³,Krishnaraj N.²

Affiliation:

1. Department of Information Technology, Manipal Institute of Technology Bengaluru, Manipal Academy of Higher Education, Manipal 576104, Karnataka, India

2. School of Computer Science and Engineering, Vellore Institute of Technology, Vellore 632014, Tamil Nadu, India

3. Department of Computer Science and Engineering, Manipal Institute of Technology Bengaluru, Manipal Academy of Higher Education, Manipal 576104, Karnataka, India

Publisher

MDPI

Link

https://www.mdpi.com/2673-4591/59/1/203/pdf

Reference20 articles.

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2. Feichtenhofer, C., Fan, H., Malik, J., and He, K. (November, January 27). Slowfast networks for video recognition. Proceedings of the IEEE/CVF International Conference on Computer Vision (ICCV), Seoul, Repulic of Korea.

3. Kay, W., Carreira, J., Simonyan, K., Zhang, B., Hillier, C., Vijayanarasimhan, S., Viola, F., Green, T., Back, T., and Natsev, P. (2017). The kinetics human action video dataset. arXiv.

4. Carreira, J., and Zisserman, A. (2017, January 21–26). Quo vadis, action recognition? a new model and the kinetics dataset. Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR), Honolulu, HI, USA.

5. Internal transfer learning for improving performance in human action recognition for small datasets;Wang;IEEE Access,2017