Self-aware circular response-guided attention for robust siamese tracking-Reference-Cited by-同舟云学术

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Self-aware circular response-guided attention for robust siamese tracking

Published:2022-12-05 Issue: Volume: Page:
ISSN:0924-669X
Container-title:Applied Intelligence
language:en
Short-container-title:Appl Intell

Author:

Tan Huibin^ORCID,Wang Mengzhu,Liang Tianyi,Xu Liyang,Tang Yuhua,Lan Long,Yang Wenjing

Funder

National Natural Science Foundation of China

the National Natural Science Foundation of China

National Defense Science and Technology Innovation Fund of the Chinese Academy of Sciences

Publisher

Springer Science and Business Media LLC

Subject

Artificial Intelligence

Link

https://link.springer.com/content/pdf/10.1007/s10489-022-04314-5.pdf

Reference67 articles.

1. Abdelpakey MH, Shehata MS, Mohamed MM (2018) Denssiam: end-to-end densely-siamese network with self-attention model for object tracking. In: International symposium on visual computing, Springer, pp 463–473

2. Bertinetto L, Valmadre J, Henriques JF, Vedaldi A, Torr PH (2016) Fully-convolutional siamese networks for object tracking. In: European conference on computer vision, Springer, pp 850–865

3. Bhat G, Danelljan M, Gool LV, Timofte R (2019) Learning discriminative model prediction for tracking. In: IEEE international conference on computer vision, pp 6182–6191

4. Chen X, Yan B, Zhu J, Wang D, Yang X, Lu H (2021) Transformer tracking. In: Proceedings of the IEEE/CVF conference on computer vision and pattern recognition, pp 8126–8135

5. Chen X, Zhang X, Tan H, Lan L, Luo Z, Huang X (2018) Multi-granularity hierarchical attention siamese network for visual tracking. In: 2018 International joint conference on neural networks (IJCNN), IEEE, pp 1–8

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1. Intelligent Robot Target Detection Algorithm Integrating TLD-GOTURN;IEEE Access;2024

2. Structural-appearance information fusion for visual tracking;The Visual Computer;2023-08-21

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