[37] Matthieu Paul, Martin Danelljan, Christoph Mayer, and Luc Van Gool. Robust visual tracking by segmentation. In Computer Vision-ECCV 2022: 17th European Conference, Tel Aviv, Israel, October 23-27, 2022, Proceedings, Part XXII, pages 571-588. Springer, 2022.
[38] Yongming Rao, Wenliang Zhao, Benlin Liu, Jiwen Lu, Jie Zhou, and Cho-Jui Hsieh. Dynamicvit: Efficient vision transformers with dynamic token sparsification. Advances in neural information processing systems, 34:13937-13949, 2021.
[39] Hamid Rezatofighi, Nathan Tsoi, JunYoung Gwak, Amir Sadeghian, Ian Reid, and Silvio Savarese. Generalized intersection over union: A metric and a loss for bounding box regression. In Proceedings of the IEEE/CVF conference on computer vision and pattern recognition, pages 658-666, 2019.
[40] Jianbing Shen, Yuanpei Liu, Xingping Dong, Xiankai Lu, Fahad Shahbaz Khan, and Steven Hoi. Distilled siamese networks for visual tracking. IEEE Transactions on Pattern Analysis and Machine Intelligence, 44(12):8896-8909, 2021.
[41] Zikai Song, Junqing Yu, Yi-Ping Phoebe Chen, and Wei Yang. Transformer tracking with cyclic shifting window attention. In Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, pages 8791-8800, 2022.
[42] Paul Voigtlaender, Jonathon Luiten, Philip HS Torr, and Bastian Leibe. Siam r-cnn: Visual tracking by re-detection. In Proceedings of the IEEE/CVF conference on computer vision and pattern recognition, pages 6578-6588, 2020.
[43] Ning Wang, Wengang Zhou, Jie Wang, and Houqiang Li. Transformer meets tracker: Exploiting temporal context for robust visual tracking. In Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, pages 1571-1580, 2021.
[44] Qiang Wang, Zhu Teng, Junliang Xing, Jin Gao, Weiming Hu, and Stephen Maybank. Learning attentions: residual attentional siamese network for high performance online visual tracking. In Proceedings of the IEEE conference on computer vision and pattern recognition, pages 4854-4863, 2018.
[45] Yi Wu, Jongwoo Lim, and Ming-Hsuan Yang. Online object tracking: A benchmark. In Proceedings of the IEEE conference on computer vision and pattern recognition, pages 2411-2418, 2013.
[46] Zhuofan Xia, Xuran Pan, Shiji Song, Li Erran Li, and Gao Huang. Vision transformer with deformable attention. In Proceedings of the IEEE/CVF conference on computer vision and pattern recognition, pages 4794-4803, 2022.
[47] Fei Xie, Chunyu Wang, Guangting Wang, Yue Cao, Wankou Yang, and Wenjun Zeng. Correlation-aware deep tracking. In Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, pages 8751-8760, 2022.
[48] Junliang Xing, Haizhou Ai, and Shihong Lao. Multiple human tracking based on multi-view upper-body detection and discriminative learning. In 2010 20th International Conference on Pattern Recognition, pages 1698-1701. IEEE, 2010.
[49] Yinda Xu, Zeyu Wang, Zuoxin Li, Ye Yuan, and Gang Yu. Siamfc++: Towards robust and accurate visual tracking with target estimation guidelines. In Proceedings of the AAAI Conference on Artificial Intelligence, volume 34, pages 12549-12556, 2020.
[50] Bin Yan, Yi Jiang, Peize Sun, Dong Wang, Zehuan Yuan, Ping Luo, and Hutchuan Lu. Towards grand unification of object tracking. In Computer Vision-ECCV 2022: 17th European Conference, Tel Aviv, Israel, October 23-27, 2022, Proceedings, Part XXI, pages 733-751. Springer, 2022.
[51] Bin Yan, Houwen Peng, Jianlong Fu, Dong Wang, and Hutchuan Lu. Learning spatio-temporal transformer for visual tracking. In Proceedings of the IEEE/CVF International Conference on Computer Vision, pages 10448-10457, 2021.
[52] Tianyu Yang and Antoni B Chan. Learning dynamic memory networks for object tracking. In Proceedings of the European conference on computer vision (ECCV), pages 152-167, 2018.
[53] Zongxin Yang, Yunchao Wei, and Yi Yang. Collaborative video object segmentation by foreground-background integration. In European Conference on Computer Vision, pages 332-348. Springer, 2020.
[54] Botao Ye, Hong Chang, Bingpeng Ma, Shiguang Shan, and Xilin Chen. Joint feature learning and relation modeling for tracking: A one-stream framework. In Computer Vision-ECCV 2022: 17th European Conference, Tel Aviv, Israel, October 23-27, 2022, Proceedings, Part XXII, pages 341-357. Springer, 2022.