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参考文献

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[7] Danelljan, Martin, et al. “Eco: Efficient convolution operators for tracking.” Proceedings of the IEEE conference on computer vision and pattern recognition. 2017.

矩阵可对角化啥意思[8] Bertinetto, L., Valmadre, J., Henriques, J. F., Vedaldi, A., Torr, P. H. (2016, October). Fully-convolutional siamese networks for object tracking. In European conference on computer vision (pp. 850-865). Springer, Cham.

[9] Tao, Ran, Efstratios Gavves, and Arnold WM Smeulders. “Siamese instance search for tracking.” Proceedings of the IEEE conference on computer vision and pattern recognition. 2016.矩阵可对角化啥意思

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[12] Zhang, Zhipeng, and Houwen Peng. “Deeper and wider siamese networks for real-time visual tracking.” Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition. 2019.

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[16] Fan, Heng, and Haibin Ling. “Sanet: Structure-aware network for visual tracking.” Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition Workshops. 2017.矩阵可对角化啥意思

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矩阵可对角化啥意思[18] Song, Yibing, et al. “VITAL: Visual tracking via adversarial learning.” Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition. 2018.

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矩阵可对角化啥意思[20] Wojke, Nicolai, Alex Bewley, and Dietrich Paulus. “Simple online and realtime tracking with a deep association metric.” 2017 IEEE International Conference on Image Processing (ICIP). IEEE, 2017.

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[23] Milan, Anton, et al. “Online multi-target tracking using recurrent neural networks.” Thirty-First AAAI Conference on Artificial Intelligence. 2017.矩阵可对角化啥意思

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[25] Zhu, Ji, et al. “Online multi-object tracking with dual matching attention networks.” Proceedings of the European Conference on Computer Vision (ECCV). 2018.

矩阵可对角化啥意思[26] Xu, Yihong, et al. “DeepMOT: A Differentiable Framework for Training Multiple Object Trackers.” arXiv preprint arXiv:1906.06618 (2019).

[27] He, Zhen, et al. “Tracking by Animation: Unsupervised Learning of Multi-Object Attentive Trackers.” Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition. 2019.

[28] Yoon, Young-Chul, et al. “Online Multiple Pedestrian Tracking using Deep Temporal Appearance Matching Association.” arXiv preprint arXiv:1907.00831 (2019).

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[30] Ristani, Ergys, et al. “Performance measures and a data set for multi-target, multi-camera tracking.” European Conference on Computer Vision. Springer, Cham, 2016.

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