[2] [2] HARE S，SAFFARI A，TORR P H S. Struck：Structured output tracking with kernels［C］//2011 International Conference on Computer Vision. Barcelona，Spain：IEEE，2011：263-270.

[3] [3] VOJIR T，NOSKOVA J，MATAS J. Robust scale-adaptive mean-shift for tracking［J］. Pattern Recognition Letters，2014，49：250-258.

[4] [4] BOLME D S，BEVERIDGE J R，DRAPER B A，et al. Visual object tracking using adaptive correlation filters［C］//2010 IEEE Computer Society Conference on Computer Vision and Pattern Recognition. San Francisco，CA，USA：IEEE，2010：2544-2550.

[5] [5] KRIZHEVSKY A，SUTSKEVER I，HINTON G E. Imagenet classification with deep convolutional neural networks［J］. Communications of the ACM，2017，60（6）：84-90.

[6] [6] MA C，HUANG J B，YANG X，et al. Hierarchical convolutional features for visual tracking［C］//2015 IEEE International Conference on Computer Vision（ICCV）. Santiago，Chile：IEEE，2015：3074-3082.

[7] [7] NAM H，HAN B. Learning multi-domain convolutional neural networks for visual tracking［C］//2016 IEEE Conference on Computer Vision and Pattern Recognition（CVPR）. Las Vegas，NV，USA：IEEE，2016：4293-4302.

[8] [8] 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，NV，USA：IEEE，2016：1420-1429.

[9] [9] BERTINETTO L，VALMADRE J，HENRIQUES J F，et al. Fully-convolutional siamese networks for object tracking［C］//HUA G，JéGOU H. Computer Vision-ECCV 2016 Workshops：volume 9914. Cham：Springer International Publishing，2016：850-865.

[10] [10] LI B，YAN 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. Salt Lake City，UT：IEEE，2018：8971-8980.

[11] [11] CHEN X，YAN B，ZHU J，et al. Transformer Tracking［C］//2021 IEEE/CVF Conference on Computer Vision and Pattern Recognition（CVPR）. Nashville，TN，USA：IEEE，2021：8122-8131.

[12] [12] VASWANI A，SHAZEER N，PARMAR N，et al. Attention is all you need［C］//Proceedings of the 31st International Conference on Neural Information Processing Systems. Red Hook，NY，USA：Curran Associates Inc.，2017：6000-6010.

[13] [13] WU Y，LIM J，YANG M H. Online object tracking：A benchmark［C］//2013 IEEE conference on computer vision and pattern recognition. Portland，OR，USA：IEEE，2013：2411-2418.

[14] [14] WU Y，LIM J，YANG M H. Object tracking benchmark［J］. IEEE Transactions on Pattern Analysis and Machine Intelligence，2015，37（9）：1834-1848.

[15] [15] KRISTAN M，LEONARDIS A，MATAS J，et al. The tenth visual object tracking VOT2022 challenge results［C］//KARLINSKY L，MICHAELI T，NISHINO K. Computer Vision - ECCV 2022 Workshops. Cham：Springer Nature Switzerland，2023：431-460.

[16] [16] KRISTAN M，MATAS J，LEONARDIS A，et al. The seventh visual object tracking VOT2019 challenge results［C］//2019 IEEE/CVF International Conference on Computer Vision Workshop（ICCVW）. Seoul，Korea（South）：IEEE，2019：2206-2241.

[17] [17] KRISTAN M，LEONARDIS A，MATAS J，et al. The eighth visual object tracking VOT2020 challenge results［C］//Computer Vision-ECCV 2020 Workshops：Glasgow，UK，August 23-28，2020，Proceedings，Part V 16. Springer，2020：547-601.

[18] [18] KRISTAN M，MATAS J，LEONARDIS A，et al. The ninth visual object tracking VOT2021 challenge results［C］//2021 IEEE/CVF International Conference on Computer Vision Workshops（ICCVW）. Montreal，BC，Canada：IEEE，2021：2711-2738.

[19] [19] MUELLER M，SMITH N，GHANEM B. A benchmark and simulator for UAV tracking［C］//LEIBE B，MATAS J，SEBE N，et al. Computer Vision-ECCV 2016. Cham：Springer International Publishing，2016：445-461.

[20] [20] MULLER M，BIBI A，GIANCOLA S，et al. Trackingnet：A large-scale dataset and benchmark for object tracking in the wild［C］//Proceedings of the European conference on computer vision（ECCV）. 2018：300-317.

[21] [21] HUANG L，ZHAO X，HUANG K. GOT-10k：A large high-diversity benchmark for generic object tracking in the wild［J］. IEEE Transactions on Pattern Analysis and Machine Intelligence，2021，43（5）：1562-1577.

[22] [22] FAN H，LIN L，YANG F，et al. Lasot：A high-quality benchmark for large-scale single object tracking［C］//Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition. 2019：5374-5383.

[23] [23] HENRIQUES J F，CASEIRO R，MARTINS P，et al. Exploiting the circulant structure of tracking-by-detection with kernels［C］//FITZGIBBON A，LAZEBNIK S，PERONA P，et al. Computer Vision-ECCV 2012：volume 7575. Berlin，Heidelberg：Springer Berlin Heidelberg，2012：702-715.

[24] [24] 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，2015，37（3）：583-596.

[25] [25] DANELLJAN M，KHAN F S，FELSBERG M，et al. Adaptive color attributes for real-time visual tracking［C］//2014 IEEE Conference on Computer Vision and Pattern Recognition. Columbus，OH：IEEE，2014：1090-1097.

[26] [26] LI Y，ZHU J. A scale adaptive kernel correlation filter tracker with feature integration［C］//AGAPITO L，BRONSTEIN M M，ROTHER C. Computer Vision-ECCV 2014 Workshops：volume 8926. Cham：Springer International Publishing，2015：254-265.

[27] [27] 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，NV，USA：IEEE，2016：1401-1409.

[28] [28] DANELLJAN M，ROBINSON A，SHAHBAZ KHAN F，et al. Beyond correlation filters：Learning continuous convolution operators for visual tracking［M］//LEIBE B，MATAS J，SEBE N，et al. Computer Vision-ECCV2016：volume 9909. Cham：Springer International Publishing，2016：472-488.

[29] [29] DANELLJAN M，BHAT G，KHAN F S，et al. ECO：Efficient convolution operators for tracking［C］//2017 IEEE Conference on Computer Vision and Pattern Recognition（CVPR）. Honolulu，HI：IEEE，2017：6931-6939.

[30] [30] BHAT G，JOHNANDER J，DANELLJAN M，et al. Unveiling the power of deep tracking［C］//FERRARI V，HEBERT M，SMINCHISESCU C， et al. Computer Vision-ECCV 2018： volume 11206. Cham： Springer International Publishing，2018：493-509.

[31] [31] BAI S，HE Z，DONG Y，et al. Multi-hierarchical independent correlation filters for visual tracking［C］//2020 IEEE International Conference on Multimedia and Expo（ICME）. London，UK：IEEE，2020：1-6.

[32] [32] DANELLJAN M，H?GER G，KHAN F S，et al. Discriminative scale space tracking［J］. IEEE Transactions on Pattern Analysis and Machine Intelligence，2017，39（8）：1561-1575.

[33] [33] DANELLJAN M，HAGER G，KHAN F S，et al. Learning spatially regularized correlation filters for fisual tracking［C］//2015 IEEE International Conference on Computer Vision（ICCV）. Santiago，Chile：IEEE，2015：4310-4318.

[34] [34] DANELLJAN M，HAGER G，KHAN F S，et al. Adaptive decontamination of the rraining set：A unified formulation for discriminative visual tracking［C］//2016 IEEE Conference on Computer Vision and Pattern Recognition（CVPR）. Las Vegas，NV，USA：IEEE，2016：1430-1438.

[35] [35] DANELLJAN M，HAGER G，KHAN F S，et al. Convolutional features for correlation filter based visual tracking［C］//2015 IEEE International Conference on Computer Vision Workshop （ICCVW）. Santiago，Chile：IEEE，2015：621-629.

[36] [36] GALOOGAHI H K，SIM T，LUCEY S. Correlation filters with limited boundaries［C］//2015 IEEE Conference on Computer Vision and Pattern Recognition（CVPR）. Boston，MA，USA：IEEE，2015：4630-4638.

[37] [37] GALOOGAHI H K，FAGG A，LUCEY S. Learning background-aware correlation filters for visual tracking［C］//2017 IEEE International Conference on Computer Vision（ICCV）. Venice：IEEE，2017：1144-1152.

[38] [38] LUKEZIC A，VOJIR T，ZAJC L C，et al. Discriminative correlation filter with channel and spatial reliability［C］//2017 IEEE Conference on Computer Vision and Pattern Recognition（CVPR）. Honolulu，HI：IEEE，2017：4847-4856.

[39] [39] LI F，TIAN C，ZUO W，et al. Learning spatial-temporal regularized correlation filters for visual tracking［C］//2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition. Salt Lake City，UT，USA：IEEE，2018：4904-4913.

[40] [40] GUNDOGDU E，ALATAN A A. Good features to correlate for visual tracking［J］. IEEE Transactions on Image Processing，2018，27（5）：2526-2540.

[41] [41] WANG M，LIU Y，HUANG Z. Large margin object rracking with circulant feature maps［C］//2017 IEEE Conference on Computer Vision and Pattern Recognition（CVPR）. Honolulu，HI：IEEE，2017：4800-4808.

[42] [42] LECUN Y，BOTTOU L，BENGIO Y，et al. Gradient-based learning applied to document recognition［J］.Proceedings of the IEEE，1998，86（11）：2278-2324.

[43] [43] FAN H，LING H. SANet：Structure-aware network for visual tracking［C］//2017 IEEE Conference on Computer Vision and Pattern RecognitionWorkshops（CVPRW）. Honolulu，HI，USA：IEEE，2017：2217-2224.

[44] [44] NAM H，BAEK M，HAN B. Modeling and propagating CNNs in a tree structure for visual tracking［M/OL］.arXiv，2016［2023-06-19］. http：//arxiv.org/abs/1608.07242.

[45] [45] DANELLJAN M，BHAT G，KHAN F S，et al. ATOM：Accurate tracking by overlap maximization［C］//2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition（CVPR）. Long Beach，CA，USA：IEEE，2019：4655-4664.

[46] [46] BHAT G，DANELLJAN M，VAN GOOL L，et al. Learning discriminative model prediction for tracking［C］//2019 IEEE/CVF International Conference on Computer Vision（ICCV）. Seoul，Korea（South）：IEEE，2019：6181-6190.

[47] [47] JIANG B，LUO R，MAO J，et al. Acquisition of localization confidence for accurate object detection［C］//FERRARI V，HEBERT M，SMINCHISESCU C，et al. Computer Vision-ECCV 2018：volume 11218. Cham：Springer International Publishing，2018：816-832.

[48] [48] MA Z，WANG L，ZHANG H，et al. RPT：Learning point set representation for siamese visual tracking［C］//BARTOLI A，FUSIELLO A. Computer Vision-ECCV 2020 Workshops. Cham：Springer International Publishing，2020：653-665.

[49] [49] LUKEZIC A，MATAS J，KRISTAN M. D3S-A discriminative single shot segmentation tracker［C］//2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition（CVPR）. Seattle，WA，USA：IEEE，2020：7131-7140.

[50] [50] YANG Z，LIU S，HU H，et al. RepPoints：Point set representation for object detection［C］//2019 IEEE/CVF International Conference on Computer Vision（ICCV）. Seoul，Korea（South）：IEEE，2019：9656-9665.

[51] [51] OH S W，LEE J Y，XU N，et al. Video object segmentation using space-time memory networks［C］//2019 IEEE/CVF International Conference on Computer Vision（ICCV）. Seoul，Korea（South）：IEEE，2019：9225-9234.

[52] [52] YAN B，ZHANG X，WANG D，et al. Alpha-refine：Boosting tracking performance by precise bounding box estimation［C］//2021 IEEE/CVF Conference on Computer Vision and Pattern Recognition（CVPR）. Nashville，TN，USA：IEEE，2021：5285-5294.

[53] [53] 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，HI：IEEE，2017：5000-5008.

[54] [54] GIRSHICK R. Fast R-CNN［C］//2015 IEEE International Conference on Computer Vision（ICCV）. Santiago，Chile，2015：1440-1448.

[55] [55] WANG Q，ZHANG L，BERTINETTO L，et al. Fast online object tracking and segmentation：A unifying approach［C］//2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition（CVPR）. Long Beach，CA，USA：IEEE，2019：1328-1338.

[56] [56] YANG T，CHAN A B. Recurrent filter learning for visual tracking［C］//2017 IEEE International Conference on Computer VisionWorkshops（ICCVW）. Venice：IEEE，2017：2010-2019.

[57] [57] HOCHREITER S，SCHMIDHUBER J. Long short-term memory［J］. Neural Computation，1997，9（8）：1735-1780.

[58] [58] DOSOVITSKIY A，BEYER L，KOLESNIKOV A，et al. An image is worth 16×16 words：Transformers for image recognition at scale［C］//International Conference on Learning Representations.Vienna，Austria，2021.

[59] [59] LIU Z，LIN Y，CAO Y，et al. Swin transformer：Hierarchical vision transformer using shifted windows［C］//2021 IEEE/CVF International Conference on Computer Vision（ICCV）. Montreal，QC，Canada：IEEE，2021：9992-10002.

[60] [60] YAN B，PENG H，FU J，et al. Learning spatio-temporal transformer for vsual tracking［C］//2021 IEEE/CVF International Conference on Computer Vision（ICCV）. Montreal，QC，Canada：IEEE，2021：10428-10437.

[61] [61] YE B，CHANG H，MA B，et al. Joint feature learning and relation modeling for tracking：A one-stream framework［C］//AVIDAN S，BROSTOW G，CISSé M，et al. Computer Vision-ECCV 2022. Cham：Springer Nature Switzerland，2022：341-357.

[62] [62] SONG Y，MA C，WU X，et al. VITAL：VIsual tracking via adversarial learning［C］//2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition. Salt Lake City，UT：IEEE，2018：8990-8999.

[63] [63] WANG X，LI C，LUO B，et al. SINT++：Robust visual tracking via adversarial positive instance generation［C］//2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition. Salt Lake City，UT：IEEE，2018：4864-4873.

[64] [64] GOU J，YU B，MAYBANK S J，et al. Knowledge distillation：A survey［J］. International Journal of Computer

[65] [65] DUNNHOFER M，MARTINEL N，MICHELONI C. Tracking-by-trackers with a distilled and reinforced model ［M］//ISHIKAWA H，LIU C L，PAJDLA T，et al. Computer Vision-ACCV 2020：volume 12623. Cham：Springer International Publishing，2021：631-650.

[66] [66] WU Z，PAN S，CHEN F，et al. A comprehensive survey on graph neural networks［J］. IEEE Transactions on Neural Networks and Learning Systems，2021，32（1）：4-24.

[67] [67] GAO J，ZHANG T，XU C. Graph convolutional tracking［C］//2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition（CVPR）. Long Beach，CA，USA：IEEE，2019：4644-4654.

[68] [68] ELSKEN T，METZEN J H，HUTTER F. Neural architecture search：A survey［J］. The Journal of Machine Learning Research，2019，20（1）：1997-2017.

[69] [69] YAN B，PENG H，WU K，et al. LightTrack：Finding lightweight neural networks for object tracking via one-shot architecture search［C］//2021 IEEE/CVF Conference on Computer Vision and Pattern Recognition （CVPR）.Nashville，TN，USA：IEEE，2021：15175-15184.