[2] [2] FU C H, LU K H, ZHENG G Z, et al. Siamese object tracking for unmanned aerial vehicle: a review and comprehensive analysis [R]. Los Alamos: arXiv Preprint, 2022: arXiv: 2205. 04281.

[3] [3] TAO R, GAVVES E, SMEULDERS A W M. Siamese instance search for tracking [C]//2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR). Las Vegas: IEEE, 2016: 1420-1429.

[4] [4] BERTINETTO L, VALMADRE J, HENRIQUES J F, et al. Fully-convolutional Siamese networks for object tracking [C]//European Conference on Computer Vision(ECCV). Cham: Springer, 2016: 850-865.

[5] [5] 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: IEEE, 2018: 8971-8980.

[6] [6] ZENG Y L, ZENG B, HU H T, et al. PRAT: accurate object tracking based on progressive attention [J]. Engineering Applications of Artificial Intelligence, 2023, 126(PC). doi: 10.1016/j.engappai.2023.106988.

[8] [8] YAN S L, QI Y J, LIU M X, et al. Object tracking based on Siamese network with 3D attention and multiple graph attention [J]. Computer Vision and Image Understanding, 2023, 235. doi:10.1016/j.cviu.2023.103786.

[9] [9] KRIZHEVSKY A, SUTSKEVER I, HINTON G E. Imagenet classification with deep convolutional neural networks [J]. Communications of the ACM, 2017, 60(6):84-90.

[10] [10] ZHANG Z P, PENG H W. Deeper and wider Siamese networks for real-time visual tracking [C]//IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR). Long Beach: IEEE, 2019: 4591-4600.

[11] [11] SZEGEDY C, LIU W, JIA Y Q, et al. Going deeper with convolutions [C]//2015 IEEE Conference on Computer Vision and Pattern Recognition (CVPR). Boston: IEEE, 2015. doi: 10.1109/CVPR.2015.7298594.

[12] [12] HE K M, ZHANG X Y, REN S Q, et al. Deep residual learning for image recognition [C]//2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR). Las Vegas: IEEE, 2016. doi: 10.1109/CVPR.2016.90.

[14] [14] CHEN F, WANG X D, ZHAO Y X, et al. Visual object tracking: a survey [J]. Computer Vision and Image Understanding, 2022, 222. doi: 10.1016/j.cviu.2022.103508.

[15] [15] LUO Y, XIAO H, OU J X, et al. SiamSMDFFF: Siamese network tracker based on shallow-middle-deep three-level feature fusion and clustering-based adaptive rectangular window filtering [J]. Neurocomputing, 2022, 483: 160-170.

[16] [16] CAO J M, LI Y Y, SUN M C, et al. DO-Conv: depthwise over-parameterized convolutional layer [J]. IEEE Transactions on Image Processing, 2022, 31: 3726-3736.

[17] [17] DAI Y M, GIESEKE F, OEHMCKE S, et al. Attentional feature fusion [R]. Los Alamos: arXiv Preprint, 2021: arXiv: 2009. 14082.

[18] [18] CAO Y, XU J R, LIN S, et al. GCNet: non-local networks meet squeeze-excitation networks and beyond [R]. Los Alamos: arXiv Preprint, 2019: arXiv: 1904. 11492.

[19] [19] KRISTAN M, MATAS J, LEONARDIS A, et al. The seventh visual object tracking VOT2019 challenge results [C]//IEEE/CVF International Conference on Computer Vision Workshops (ICCVW). Seoul: IEEE, 2019. doi: 10.1109/ICCVW.2019.00276.

[20] [20] ZHANG L C, GONZALEZ-GARCIA A, VAN DE WEIJER J, et al. Learning the model update for Siamese trackers [C]//2019 IEEE/CVF International Conference on Computer Vision (ICCV). Seoul: IEEE, 2019. doi: 10.1109/ICCV.2019.00411.

[21] [21] HENRIQUES J F, CASEIRO R, MARTINS P, et al. High-speed tracking with kernelized correlation filters [J]. IEEE Transactions on Pattern Analysis & Machine Intelligence, 2015, 37(3):583-596.

[22] [22] DANELLJAN M, HGER G, KHAN F S, et al. Accurate scale estimation for robust visual tracking [C]//British Machine Vision Conference(BMVC). Nottingham: BMVC, 2014. doi: 10.5244/C.28.65.

[23] [23] DANELLJAN M, HGER G, KHAN F S, et al. Learning spatially regularized correlation filters for visual tracking [C]//2015 IEEE International Conference on Computer Vision (ICCV). Santiago: IEEE, 2015. doi: 10.1109/ICCV.2015.490.

[24] [24] BERTINETTO L, VALMADRE J, GOLODETZ S, et al. Staple: complementary learners for real-time tracking [C]//2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR). Las Vegas: IEEE, 2016. doi: 10.1109/CVPR.2016.156.

[25] [25] ZHANG J M, MA S G, SCLAROFF S. MEEM: robust tracking via multiple experts using entropy minimization [C]//European Conference on Computer Vision(ECCV). Cham: Springer, 2014: 188-203.

[26] [26] GUO Q, FENG W, ZHOU C, et al. Learning dynamic Siamese network for visual object tracking [C]//2017 IEEE International Conference on Computer Vision (ICCV). Venice: IEEE, 2017. doi: 10.1109/ICCV.2017.196.

[27] [27] LI Y H, ZHANG X F, CHEN D M. SiamVGG: visual tracking using deeper Siamese networks [R]. Los Alamos: arXiv Preprint, 2019: arXiv: 1902. 02804.

[28] [28] 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). Honolulu: IEEE, 2017. doi: 10.1109/CVPR.2017.531.

[29] [29] DANELLJAN M, BHAT G, KHAN S F, et al. ECO: efficient convolution operators for tracking [C]//2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR). Honolulu: IEEE, 2017. doi: 10.1109/CVPR.2017.733.