• Acta Optica Sinica
  • Vol. 40, Issue 19, 1915001 (2020)
Zhoujuan Cui1、2、*, Junshe An1, Yufeng Zhang1、2, and Tianshu Cui1、2
Author Affiliations
  • 1Key Laboratory of Electronics and Information Technology for Space Systems, National Space Science Center, Chinese Academy of Sciences, Beijing 100190, China
  • 2University of Chinese Academy of Sciences, Beijing 100049, China
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    DOI: 10.3788/AOS202040.1915001 Cite this Article Set citation alerts
    Zhoujuan Cui, Junshe An, Yufeng Zhang, Tianshu Cui. Light-Weight Siamese Attention Network Object Tracking for Unmanned Aerial Vehicle[J]. Acta Optica Sinica, 2020, 40(19): 1915001 Copy Citation Text show less
    References

    [1] Henriques J F, Caseiro R, Martins P et al. Exploiting the circulant structure of tracking-by-detection with kernels[J]. Computer Vision-ECCV, 2012, 702-715(2012). http://dl.acm.org/citation.cfm?id=2404742.2404795

    [2] Henriques J F, Caseiro R, Martins P et al. High-speed tracking with kernelized correlation filters[J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 37, 583-596(2015).

    [3] Ma C, Huang J B, Yang X K et al. Hierarchical convolutional features for visual tracking[C]//2015 IEEE International Conference on Computer Vision (ICCV). December 7-13, 2015, Santiago, Chile., 3074-3082(2015).

    [4] Nam H, Han B. Learning multi-domain convolutional neural networks for visual tracking[C]//2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR). June 27-30, 2016, Las Vegas, NV, USA., 4293-4302(2016).

    [5] Danelljan M, Robinson A, Shahbaz Khan F et al. Beyond correlation filters: learning continuous convolution operators for visual tracking[J]. Computer Vision-ECCV, 2016, 472-488(2016).

    [6] DanelljanM, BhatG, Khan FS, et al.ECO: efficient convolution operators for tracking[C]//2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR). July 21-26, 2017, Honolulu, HI, USA. New York: IEEE Press, 2017: 6931- 6939.

    [7] Tao R, Gavves E. Smeulders A W M. Siamese instance search for tracking[C]//2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR). June 27-30, 2016, Las Vegas, NV, USA., 1420-1429(2016).

    [8] Bertinetto L, Valmadre J, Henriques J F et al[M]. Fully-convolutional Siamese networks for object tracking, 850-865(2016).

    [9] Valmadre J, Bertinetto L, Henriques J et al. End-to-end representation learning for correlation filter based tracking[C]//2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR). July 21-26, 2017, Honolulu, HI, USA., 5000-5008(2017).

    [10] Li B, Yan J J, Wu W et al. High performance visual tracking with Siamese region proposal network. [C]//2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition(CVPR), Salt Lake City, USA, 8971-8980(2018).

    [11] Qiu Z L, Zha Y F, Zhu P et al. Visual tracking algorithm based on online feature discrimination with siamese network[J]. Acta Optica Sinica, 39, 0915003(2019).

    [12] Chen Z W, Zhang Z X, Song J et al. Tracking algorithm for siamese network based on target-aware feature selection[J]. Acta Optica Sinica, 40, 0915003(2020).

    [13] Sandler M, Howard A, Zhu M L, linear bottlenecks[EB/OL] et al. -03-21)[2020-05-13], org/abs/1801, 04381(2019). https://arxiv.

    [14] Howard A G, Zhu M L, Chen B et al. -04-17)[2020-05-13], org/abs/1704, 04861(2017). https://arxiv.

    [15] Selvaraju R R, Cogswell M, Das A et al. Grad-CAM: visual explanations from deep networks via gradient-based localization[J]. International Journal of Computer Vision, 128, 336-359(2020).

    [16] Woo S, Park J, Lee J Y et al. CBAM: convolutional block attention module. [C]//European Conference on Computer Vision, 3-19(2018).

    [17] Krizhevsky A, Sutskever I, Hinton G E. ImageNet classification with deep convolutional neural networks[J]. Communications of the ACM, 60, 84-90(2017).

    [18] Real E, Shlens J, Mazzocchi S et al. YouTube-, 7464-7473(2017).

    [19] Wu Y, Lim J, Yang M H. Object tracking benchmark[J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 37, 1834-1848(2015).

    [20] Danelljan M, Häger G, Khan F S et al. Learning spatially regularized correlation filters for visual tracking[C]//2015 IEEE International Conference on Computer Vision (ICCV). December 7-13, 2015, Santiago, Chile., 4310-4318(2015).

    [21] Jia X, Lu H C, Yang M H. Visual tracking via adaptive structural local sparse appearance model[C]//2012 IEEE Conference on Computer Vision and Pattern Recognition. June 16-21, 2012, Providence, RI, USA., 1822-1829(2012).

    [22] Li Y, Zhu J K. A scale adaptive kernel correlation filter tracker with feature integration[J]. Computer Vision-ECCV 2014 Workshops, 254-265(2015).

    [23] Danelljan M, Häger G, Shahbaz Khan F et al. Accurate scale estimation for robust visual tracking. [C]//Proceedings of the British Machine Vision Conference 2014. Nottingham. British Machine Vision Association, 1-11(2014).

    [24] Mueller M, Smith N, Ghanem B[M]. A benchmark and simulator for UAV tracking, 445-461(2016).

    Zhoujuan Cui, Junshe An, Yufeng Zhang, Tianshu Cui. Light-Weight Siamese Attention Network Object Tracking for Unmanned Aerial Vehicle[J]. Acta Optica Sinica, 2020, 40(19): 1915001
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