References
Bertinetto L, Valmadre J, Henriques J F, Vedaldi A, Torr P H S. Fully-convolutional siamese networks for object tracking. In: Proceedings of European Conference on Computer Vision. 2016, 850–865
Wang Q, Zhang L, Bertinetto L, Hu W, Torr P H S. Fast online object tracking and segmentation: a unifying approach. In: Proceedings of the IEEE/CUF Conference on Computer Vision and Pattern Recognition. 2019, 1328–1338
Ren S, He K, Girshick R, Sun J. Faster R-CNN: towards real-time object detection with region proposal networks. In: Proceedings of the 28th International Conference on Neural Information Processing Systems. 2015, 91–99
Margffoy-tuay E A, Perez J C, Botero E, Arbelaze P. Dynamic multimodal instance segmentation guided by natural language queries. In: Proceedings of European Conference on Computer Vision. 2018, 656–672
Tao L, Yu Z, Sida W, Hui D, Yoav A. Simple recurrent units for highly parallelizable recurrence. In: Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing. 2018, 4470–4481
Lucas B D, Kanade T. An iterative technique of image registration and its application to stereo. In: Proceedings of International Joint Conference on Artificial Intelligence.1981, 674–679
Wu Y, Lim J W, Yang M H. Object tracking benchmark. IEEE Transactions on Pattern Analysis & Machine Intelligence, 2015, 37(9): 1834–1848
Fan H, Lin L, Yang F, Chu P, Deng G, Yu S. LaSOT: a high-quality benchmark for large-scale single object Tracking. In: Proceedings of the IEEE/CUF Conference on Computer Vision and Pattern Recognition. 2018, 5374–5383
Kazemzadeh S, Ordonez V, Matten M, Berg T. Referitgame: referring to objects in photographs of natural scenes. In: Proceedings of the 2014 Conference on Empirical Methods in Natural Language Processing. 2014, 787–798
Licheng Y, Patric P, Shan Y, Alexander B, Tamara B. Modeling context in referring expressions. In: Proceedings of European Conference on Computer Vision. 2016, 69–85
Junhua M, Jonathan H, Alexander T, Oana C, Kevin M. Generation and comprehension of unambiguous object descriptions. In: Proceedings of the 2016 IEEE Conference on Computer Vision and Pattern Recognition. 2016, 11–20
Acknowledgements
This work was supported in part by the National Natural Science Foundation of China (Grant No. 62076246).
Author information
Authors and Affiliations
Corresponding author
Rights and permissions
About this article
Cite this article
Zhou, Q., Wang, R., Li, J. et al. Siamese single object tracking algorithm with natural language prior. Front. Comput. Sci. 15, 155335 (2021). https://doi.org/10.1007/s11704-020-0027-8
Received:
Accepted:
Published:
DOI: https://doi.org/10.1007/s11704-020-0027-8