Learning discriminative correlation filters via saliency-aware channel selection for robust visual object tracking-Reference-Cited by-同舟云学术

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Learning discriminative correlation filters via saliency-aware channel selection for robust visual object tracking

Published:2023-05-05 Issue:3 Volume:20 Page:
ISSN:1861-8200
Container-title:Journal of Real-Time Image Processing
language:en
Short-container-title:J Real-Time Image Proc

Author:

Ma Sugang,Zhao Zhixian,Pu Lei,Hou Zhiqiang,Zhang Lei,Zhao Xiangmo

Funder

National Natural Science Foundation of China

Science and Technology Project of Xi’an City

Natural Science Foundation of Shaanxi Province

Publisher

Springer Science and Business Media LLC

Subject

Information Systems

Link

https://link.springer.com/content/pdf/10.1007/s11554-023-01306-7.pdf

Reference58 articles.

1. Fiaz, M., Mahmood, A., Javed, S.: Jung SK Handcrafted and deep trackers: Recent visual object tracking approaches and trends. ACM Comput. Surv. 52(2), 1–44 (2019)

2. Ahmed, I.: Jeon G A real-time person tracking system based on siammask network for intelligent video surveillance. J. Real-Time Image Process 18(5), 1803–1814 (2021)

3. Zhang, Z., Zhang, Y., Cheng, X.: Li K Siamese network for real-time tracking with action-selection. J. Real-Time Image Process 17(5), 1647–1657 (2020)

4. Lin, B., Xue, X., Li, Y.: Shen Q Learning correlation filter with fused feature and reliable response for real-time tracking. J. Real-Time Image Process 19(2), 417–427 (2022)

5. Bertinetto, L., Valmadre, J., Golodetz, S., Miksik, O., Torr, P.H., Staple: Complementary learners for real-time tracking. In: Proc. IEEE Conf. Comput. Vis. Pattern Recognit. (CVPR), pp 1401–1409 (2016)

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