Self-supervised discriminative model prediction for visual tracking
Author:
Funder
National Natural Science Foundation of China
Postdoctoral Research Foundation of China
Publisher
Springer Science and Business Media LLC
Subject
Artificial Intelligence,Software
Link
https://link.springer.com/content/pdf/10.1007/s00521-023-09348-5.pdf
Reference47 articles.
1. Yuan D, Shu X, Liu Q, Zhang X, He Z (2023) Robust thermal infrared tracking via an adaptively multi-feature fusion model. Neural Comput Appl 35:3423–3434
2. Li B, Wu W, Wang Q, Zhang F, Xing J, Yan J (2019) Siamrpn++: evolution of siamese visual tracking with very deep networks. In: Proceedings of the IEEE/CVF conference on computer vision and pattern recognition, pp 4282–4291
3. Xu L, Gao M, Liu Z, Li Q, Jeon G (2022) Accelerated duality-aware correlation filters for visual tracking. Neural Comput Appl. https://doi.org/10.1007/s00521-021-06794-x
4. Yuan D, Li X, He Z, Liu Q, Lu S (2020) Visual object tracking with adaptive structural convolutional network. Knowl Based Syst 194:105554
5. Bhat G, Danelljan M, Van Gool L, Timofte R (2019) Learning discriminative model prediction for tracking. In: Proceedings of the IEEE/CVF international conference on computer vision, pp 6181–6190
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