Refiner: a general object position refinement algorithm for visual tracking
Author:
Funder
Shaanxi Key Research and Development Program
Publisher
Springer Science and Business Media LLC
Subject
Artificial Intelligence,Software
Link
https://link.springer.com/content/pdf/10.1007/s00521-023-09263-9.pdf
Reference69 articles.
1. Wu Y, Lim J, Yang M-H (2015) Object tracking benchmark. IEEE Trans Pattern Anal Mach Intell 37(9):1834–1848. https://doi.org/10.1109/TPAMI.2014.2388226
2. Danelljan M, Van Gool L, Timofte R (2020) Probabilistic regression for visual tracking. In: 2020 IEEE/CVF Conference on computer vision and pattern recognition (CVPR). https://doi.org/10.1109/CVPR42600.2020.00721
3. Mayer C, Danelljan M, Bhat G, Paul M, Paudel DP, Yu F, Gool LV (2022) Transforming model prediction for tracking. In: 2022 IEEE/CVF Conference on computer vision and pattern recognition (CVPR). https://doi.org/10.1109/CVPR52688.2022.00853
4. Chen X, Yan B, Zhu J, Wang D, Yang X, Lu H (2021) Transformer tracking. In: 2021 IEEE/CVF Conference on computer vision and pattern recognition (CVPR), pp 8126–8135. https://doi.org/10.1109/CVPR46437.2021.00803
5. Danelljan M, Bhat G, Khan FS, Felsberg M (2017) ECO: efficient convolution operators for tracking. In: 2017 IEEE/CVF Conference on computer vision and pattern recognition (CVPR), pp 6931–6939. https://doi.org/10.1109/CVPR.2017.733
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