[1] Li X, Zha Y F, Zhang T Z et al. Survey of visual object tracking algorithms based on deep learning[J]. Journal of Image and Graphics, 24, 2057-2080(2019).
[2] Kalal Z, Mikolajczyk K, Matas J. Tracking-learning-detection[J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 34, 1409-1422(2012).
[3] Hare S, Torr P H S. Struck: structured output tracking with kernels[C], 263-270(2011).
[4] 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).
[5] Danelljan M, Häger G, Khan F S et al. Accurate scale estimation for robust visual tracking[C](2014).
[6] Danelljan M, Häger G, Khan F S et al. Learning spatially regularized correlation filters for visual tracking[C], 4310-4318(2015).
[7] Ma C, Yang X K, Zhang C Y et al. Long-term correlation tracking[C], 5388-5396(2015).
[8] Hong Z B, Chen Z, Wang C H et al. MUlti-Store Tracker (MUSTer): a cognitive psychology inspired approach to object tracking[C], 749-758(2015).
[9] Danelljan M, Häger G, Khan F S et al. Discriminative scale space tracking[J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 39, 1561-1575(2017).
[10] Lukežič A, Vojíř T, Zajc L Č et al. Discriminative correlation filter tracker with channel and spatial reliability[J]. International Journal of Computer Vision, 126, 671-688(2018).
[11] Li F, Tian C, Zuo W M et al. Learning spatial-temporal regularized correlation filters for visual tracking[C], 4904-4913(2018).
[12] Li Y M, Fu C H, Ding F Q et al. AutoTrack: towards high-performance visual tracking for UAV with automatic spatio-temporal regularization[C], 11920-11929(2020).
[13] Liu Z D, Dong L Q, Zhao Y J et al. Adaptive model tracking algorithm for fast-moving targets in video[J]. Acta Optica Sinica, 41, 1815001(2021).
[14] Danelljan M, Häger G, Khan F S et al. Convolutional features for correlation filter based visual tracking[C], 621-629(2015).
[15] Danelljan M, Robinson A, Khan F S et al. Beyond correlation filters: learning continuous convolution operators for visual tracking[M]. Leibe B, Matas J, Sebe N, et al. Computer vision-ECCV 2016. Lecture notes in computer science, 9909, 472-488(2016).
[16] Danelljan M, Bhat G, Khan F S et al. ECO: efficient convolution operators for tracking[C], 6931-6939(2017).
[17] Bhat G, Johnander J, Danelljan M et al. Unveiling the power of deep tracking[M]. Ferrari V, Hebert M, Sminchisescu C, et al. Computer vision-ECCV 2018. Lecture notes in computer science, 11206, 493-509(2018).
[18] Nam H, Han B. Learning multi-domain convolutional neural networks for visual tracking[C], 4293-4302(2016).
[19] Tao R, Gavves E, Smeulders A W M. Siamese instance search for tracking[C], 1420-1429(2016).
[20] 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, 9914, 850-865(2016).
[21] Valmadre J, Bertinetto L, Henriques J et al. End-to-end representation learning for correlation filter based tracking[C], 5000-5008(2017).
[22] Li B, Yan J J, Wu W et al. High performance visual tracking with siamese region proposal network[C], 8971-8980(2018).
[23] 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, 11213, 103-119(2018).
[24] Li B, Wu W, Wang Q et al. SiamRPN: evolution of siamese visual tracking with very deep networks[C], 4277-4286(2019).
[25] Xu Y D, Wang Z Y, Li Z X et al. SiamFC++: towards robust and accurate visual tracking with target estimation guidelines[J]. Proceedings of the AAAI Conference on Artificial Intelligence, 34, 12549-12556(2020).
[26] Zhang Z P, Peng H W, Fu J L et al. Ocean: object-aware anchor-free tracking[M]. Vedaldi A, Bischof H, Brox T, et al. Computer vision-ECCV 2020. Lecture notes in computer science, 12366, 771-787(2020).
[27] Li C, Yang D D, Song P et al. Global-aware siamese network for thermal infrared object tracking[J]. Acta Optica Sinica, 41, 0615002(2021).
[28] Zheng J S, Guo H, Li A B et al. Real-time tracking of fast moving weak object based on siamese network[J]. Laser & Optoelectronics Progress, 59, 0410011(2022).
[29] Felzenszwalb P F, Girshick R B, McAllester D et al. Object detection with discriminatively trained part-based models[J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 32, 1627-1645(2010).
[30] Kroeger T, Timofte R, Dai D et al. Fast optical flow using dense inverse search[M]. Leibe B, Matas J, Sebe N, et al. Computer vision-ECCV 2016. Lecture notes in computer science, 9908, 471-488(2016).
[31] Lucas B D, Kanade T. An iterative image registration technique with an application to stereo vision[C], 674-679(1981).
[32] Du D, Zhu P, Wen L et al. VisDrone-SOT2019: the vision meets drone single object tracking challenge results[C], 199-212(2019).