A Spatio-Temporal Robust Tracker with Spatial-Channel Transformer and Jitter Suppression
Author:
Funder
National Natural Science Foundation of China
Publisher
Springer Science and Business Media LLC
Subject
Artificial Intelligence,Computer Vision and Pattern Recognition,Software
Link
https://link.springer.com/content/pdf/10.1007/s11263-023-01902-x.pdf
Reference58 articles.
1. Bai, S., He, Z., Dong, Y., & Bai, H. (2020). Multi-hierarchical independent correlation filters for visual tracking. In 2020 IEEE international conference on multimedia and expo (ICME) (pp. 1–6).
2. Bertinetto, L., Valmadre, J., Henriques, J. F., Vedaldi, A., & Torr, P. H. (2016). Fully-convolutional Siamese networks for object tracking. In European conference on computer vision. Springer (pp. 850–865).
3. Bhat, G., Johnander, J., Danelljan, M., Khan, F. S. & Felsberg, M. (2018). Unveiling the power of deep tracking. In European conference on computer vision (pp. 493–509).
4. Bhat, G., Danelljan, M., Van Gool, L. & Timofte, R. (2020). Know your surroundings: Exploiting scene information for object tracking. In European conference on computer vision (pp. 205–221).
5. Carion, N., Massa, F., Synnaeve, G., Usunier, N., Kirillov, A. & Zagoruyko, S. (2020). End-to-end object detection with transformers. In: Vedaldi, A., Bischof, H., Brox, T., Frahm, J.M. (Eds) European conference on computer vision (pp. 213–229).
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