[1] 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, June 13-18, 2010, San Francisco, CA, USA., 2544-2550(2010).

[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] 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, June 23-28, 2014, Columbus, OH, USA., 1090-1097(2014).

[4] 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).

[5] 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), June 27-30, 2016, Las Vegas, NV, USA, 1401-1409(2016).

[6] Lukežic A, Vojír 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), July 21-26, 2017, Honolulu, HI, USA., 4847-4856(2017).

[7] Xiong C Z, Che M Q, Wang R L et al. Robust real-time visual tracking via dual model adaptive switching[J]. Acta Optica Sinica, 38, 1015002(2018).

[8] Bertinetto L, Valmadre J, Henriques J F et al. Fully-convolutional siamese networks for object tracking[M]. //Hua G, Jégou H. Computer vision- ECCV 2016 workshops. Lecture notes in computer science. Cham: Springer, 9914, 850-865(2016).

[9] Wang Q, Teng Z, Xing J L et al. Learning attentions: residual attentional siamese network for high performance online visual tracking[C]. //2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition, June 18-23, 2018, Salt Lake City, UT, USA, 4854-4863(2018).

[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, June 18-23, 2018, Salt Lake City, UT, USA., 8971-8980(2018).

[11] Ren S Q, He K M, Girshick R et al. Faster R-CNN: towards real-time object detection with region proposal networks[J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 39, 1137-1149(2017).

[12] Wang Q, Gao J, Xing J L et al. DCFNet: discriminant correlation filters network for visual tracking[EB/OL]. [2020-05-03].https: //arxiv. org/pdf/1704. 04057. pdf..

[13] Zhang M, Wang Q, Xing J L et al. Visual tracking via spatially aligned correlation filters network[EB/OL]. [2020-05-03].https: //www. researchgate. net/publication/333660310_Visual_tracking_via_spatially_aligned_correlation_filters_network..

[14] 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), October 27-November 2, 2019, Seoul, Korea (South)., 6181-6190(2019).

[15] 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), October 22-29, 2017, Venice, Italy., 1781-1789(2017).

[16] Zhu Z, Wang Q, Li B et al. Distractor-aware siamese networks for visual object tracking[M]. //Ferrari V, Hebert M, Sminchisescu C, et al. Computer vision-ECCV 2018. Lecture notes in computer science. Cham: Springer, 11213, 103-119(2018).

[17] 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), June 15-20, 2019, Long Beach, CA, USA, 1328-1338(2019).

[18] 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), June 15-20, 2019, Long Beach, CA, USA, 4655-4664(2019).

[19] 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), July 21-26, 2017, Honolulu, HI, USA, 6931-6939(2017).

[20] XiongC Z, Lu Y, Yan J Q. Weighted correlation filter tracking algorithm based on context and relocation[J]. Acta Optica Sinica, 39, 0415004(2019).

[21] Wang M M, Liu Y, Huang Z Y. Large margin object tracking with circulant feature maps[C]. //2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), July 21-26, 2017, Honolulu, HI, USA., 4800-4808(2017).

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

[23] Fan H, Lin L T, Yang F et al. LaSOT: a high-quality benchmark for large-scale single object tracking[C]. //2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), June 15-20, 2019, Long Beach, CA, USA, 5369-5378(2019).

[24] Mueller M, Smit N, Ghanem B. A benchmark and simulator for UAV tracking[M]. //Leibe B, Matas J, Sebe N, et al. Computer vision-ECCV 2016. Lecture notes in computer science. Cham: Springer, 9905, 445-461(2016).

[25] Kristan M, Matas J et al. The sixth visual object tracking VOT2018 challenge results[M]. //Laura L T, Stefan R. Computer vision-ECCV 2018 workshops. Lecture notes in computer science. Amsterdam: Springer, 11129, 3-53(2018).

[26] Lukezic A, Kart U, Käpylä J et al. CDTB: a color and depth visual object tracking dataset and benchmark[C]. //2019 IEEE/CVF International Conference on Computer Vision (ICCV), October 27-November 2, 2019, Seoul, Korea (South), 10012-10021(2019).

[27] Xu T Y, Feng Z H, Wu X J et al. Learning adaptive discriminative correlation filters via temporal consistency preserving spatial feature selection for robust visual object tracking[J]. IEEE Transactions on Image Processing, 28, 5596-5609(2019). http://ieeexplore.ieee.org/document/8728173

[28] Li B, Wu W, Wang Q et al. SiamRPN++: evolution of Siamese visual tracking with very deep networks[C]. //2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), June 15-20, 2019, Long Beach, CA, USA., 4277-4286(2019).

[29] 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).

[30] Song Y B, Ma C, Wu X H et al. VITAL: VIsual tracking via adversarial learning[C]. //2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition, June 18-23, 2018, Salt Lake City, UT, 8990-8999(2018).

[31] 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).

[32] Galoogahi H K, Fagg A, Lucey S. Learning background-aware correlation filters for visual tracking[C]. //2017 IEEE International Conference on Computer Vision (ICCV), October 22-29, 2017, Venice, Italy., 1144-1152(2017).

[33] Fan H, Ling H B. Parallel tracking and verifying[J]. IEEE Transactions on Image Processing, 28, 4130-4144(2019).