Multiple convolutional features in Siamese networks for object tracking-Reference-Cited by-同舟云学术

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Multiple convolutional features in Siamese networks for object tracking

Published:2021-03-11 Issue:3 Volume:32 Page:
ISSN:0932-8092
Container-title:Machine Vision and Applications
language:en
Short-container-title:Machine Vision and Applications

Author:

Li Zhenxi,Bilodeau Guillaume-Alexandre^ORCID,Bouachir Wassim^ORCID

Funder

Fonds de Recherche du Québec - Nature et Technologies

Publisher

Springer Science and Business Media LLC

Subject

Computer Science Applications,Computer Vision and Pattern Recognition,Hardware and Architecture,Software

Link

https://link.springer.com/content/pdf/10.1007/s00138-021-01185-7.pdf

Reference33 articles.

1. Bertinetto, L., Valmadre, J., Golodetz, S., Miksik, O., Torr, P.H.S.: Staple: Complementary learners for real-time tracking. 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR) pp. 1401–1409 (2016)

2. Bertinetto, L., Valmadre, J., Henriques, J.F., Vedaldi, A., Torr, P.H.S.: Fully-convolutional siamese networks for object tracking. In: Hua, G., Jégou, H. (eds.) Computer Vision - ECCV 2016 Workshops, pp. 850–865. Springer, Cham (2016)

3. Choi, J., Chang, H.J., Fischer, T., Yun, S., Lee, K., Jeong, J., Demiris, Y., Choi, J.Y.: Context-aware deep feature compression for high-speed visual tracking. In: IEEE conference on computer vision and pattern recognition, pp. 479–488 (2018)

4. Deng, J., Dong, W., Socher, R., Li, L., Li, K., Fei-Fei, L.: Imagenet: a large-scale hierarchical image database. In: 2009 IEEE conference on computer vision and pattern recognition, pp. 248–255 (2009)

5. Hare, S., Golodetz, S., Saffari, A., Vineet, V., Cheng, M., Hicks, S.L., Torr, P.H.S.: Struck: structured output tracking with kernels. IEEE Trans Pattern Anal Mach Intell 38(10), 2096–2109 (2016)

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