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This paper introduces a novel deep learning based approach for vision based single target tracking.
S. Oron, A. Bar-Hillel, D. Levi, and S. Avidan, “Locally orderless tracking,” in Computer Vision and Pattern Recognition (CVPR), 2012 IEEE Conference on . IEEE, 2012, pp. 1940–1947
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K. Nummiaro, E. Koller-Meier, and L. Van Gool, “An adaptive color-based particle filter,” Image and vision computing , vol. 21, no. 1, pp. 99–110, 2003
2003
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A. D. Jepson, D. J. Fleet, and T. F. El-Maraghi, “Robust online appearance models for visual tracking,” Pattern Analysis and Machine Intelligence, IEEE Transactions on , vol. 25, no. 10, pp. 1296–1311, 2003
2003
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S. Avidan, “Support vector tracking,” Pattern Analysis and Machine Intelligence, IEEE Transactions on , vol. 26, no. 8, pp. 1064–1072, 2004
2004
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R. T. Collins, Y. Liu, and M. Leordeanu, “Online selection of discriminative tracking features,” Pattern Analysis and Machine Intelligence, IEEE Transactions on , vol. 27, no. 10, pp. 1631–1643, 2005
2005
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A. Adam, E. Rivlin, and I. Shimshoni, “Robust fragments-based tracking using the integral histogram,” in Computer vision and pattern recognition, 2006 IEEE Computer Society Conference on , vol. 1. IEEE, 2006, pp. 798–805
2006
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S. Avidan, “Ensemble tracking,” Pattern Analysis and Machine Intelligence, IEEE Transactions on , vol. 29, no. 2, pp. 261–271, 2007
2007
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D. A. Ross, J. Lim, R.-S. Lin, and M.-H. Yang, “Incremental learning for robust visual tracking,” International Journal of Computer Vision , vol. 77, no. 1-3, pp. 125–141, 2008
2008
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H. Grabner, C. Leistner, and H. Bischof, “Semi-supervised on-line boosting for robust tracking,” in Computer Vision–ECCV 2008 . Springer, 2008, pp. 234–247
2008
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A. Torralba, R. Fergus, and W. Freeman, “80 million tiny images: A large data set for nonparametric object and scene recognition,” Pattern Analysis and Machine Intelligence, IEEE Transactions on , vol. 30, no. 11, pp. 1958–1970, 2008
2008
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Z. Kalal, J. Matas, and K. Mikolajczyk, “Pn learning: Bootstrapping binary classifiers by structural constraints,” in Computer Vision and Pattern Recognition (CVPR), 2010 IEEE Conference on . IEEE, 2010, pp. 49–56
2010
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J. Kwon and K. M. Lee, “Visual tracking decomposition,” in Computer Vision and Pattern Recognition (CVPR), 2010 IEEE Conference on . IEEE, 2010, pp. 1269–1276
2010
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B. Alexe, T. Deselaers, and V. Ferrari, “What is an object?” in Computer Vision and Pattern Recognition (CVPR), 2010 IEEE Conference on . IEEE, 2010, pp. 73–80
2010
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J. Fan, W. Xu, Y. Wu, and Y. Gong, “Human tracking using convolutional neural networks,” Neural Networks, IEEE Transactions on , vol. 21, no. 10, pp. 1610–1623, 2010
2010
Cited alongside, same era.
H. Yang, L. Shao, F. Zheng, L. Wang, and Z. Song, “Recent advances and trends in visual tracking: A review,” Neurocomputing , vol. 74, no. 18, pp. 3823–3831, 2011
2011
Cited alongside, same era.
S. Hare, A. Saffari, and P. Torr, “Struck: Structured output tracking with kernels,” in Computer Vision (ICCV), 2011 IEEE International Conference on , Nov 2011, pp. 263–270
2011
Cited alongside, same era.
T. B. Dinh, N. Vo, and G. Medioni, “Context tracker: Exploring supporters and distracters in unconstrained environments,” in Computer Vision and Pattern Recognition (CVPR), 2011 IEEE Conference on . IEEE, 2011, pp. 1177–1184
2011
Cited alongside, same era.
H. Li, Y. Li, and F. Porikli, “Deeptrack: Learning discriminative feature representations by convolutional neural networks for visual tracking,” in Proceedings of the British Machine Vision Conference. BMVA Press , 2014
2014
Later among the works it cites.
T. Zhang, S. Liu, C. Xu, S. Yan, B. Ghanem, N. Ahuja, and M.-H. Yang, “Structural sparse tracking,” in Computer Vision and Pattern Recognition (CVPR), 2015 IEEE Conference on , June 2015, pp. 150–158
2015
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J. F. Henriques, R. Caseiro, P. Martins, and J. Batista, “High-speed tracking with kernelized correlation filters,” Pattern Analysis and Machine Intelligence, IEEE Transactions on , vol. 37, no. 3, pp. 583–596, 2015
2015
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H. Possegger, T. Mauthner, and H. Bischof, “In defense of color-based model-free tracking,” in Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition , 2015, pp. 2113–2120
2015
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B. Babenko, M.-H. Yang, and S. Belongie, “Robust object tracking with online multiple instance learning,” Pattern Analysis and Machine Intelligence, IEEE Transactions on , vol. 33, no. 8, pp. 1619–1632, 2011
2011
Cited alongside, same era.
K. Zhang, L. Zhang, and M.-H. Yang, “Real-time compressive tracking,” in Computer Vision–ECCV 2012 . Springer, 2012, pp. 864–877
2012
Cited alongside, same era.
A. Krizhevsky, I. Sutskever, and G. E. Hinton, “Imagenet classification with deep convolutional neural networks,” in Advances in Neural Information Processing Systems 25 , F. Pereira, C. Burges, L. Bottou, and K. Weinberger, Eds. Curran Associates, Inc., 2012, pp. 1097–1105. [Online]. Available: http://papers.nips.cc/paper/4824-imagenet-classification-with-deep-convolutional-neural-networks.pdf
2012
Cited alongside, same era.
Y. Wu, J. Lim, and M.-H. Yang, “Online object tracking: A benchmark,” in IEEE Conference on Computer Vision and Pattern Recognition (CVPR) , 2013
2013
Cited alongside, same era.
K. Zhang, L. Zhang, and M.-H. Yang, “Real-time object tracking via online discriminative feature selection,” Image Processing, IEEE Transactions on , vol. 22, no. 12, pp. 4664–4677, 2013
2013
Cited alongside, same era.
N. Wang and D.-Y. Yeung, “Learning a deep compact image representation for visual tracking,” in Advances in Neural Information Processing Systems 26 , C. Burges, L. Bottou, M. Welling, Z. Ghahramani, and K. Weinberger, Eds. Curran Associates, Inc., 2013, pp. 809–817. [Online]. Available: http://papers.nips.cc/paper/5192-learning-a-deep-compact-image-representation-for-visual-tracking.pdf
2013
Cited alongside, same era.
M. Danelljan, F. S. Khan, M. Felsberg, and J. van de Weijer, “Adaptive color attributes for real-time visual tracking,” in Computer Vision and Pattern Recognition (CVPR), 2014 IEEE Conference on . IEEE, 2014, pp. 1090–1097
2014
Cited alongside, same era.
R. Girshick, J. Donahue, T. Darrell, and J. Malik, “Rich feature hierarchies for accurate object detection and semantic segmentation,” in Computer Vision and Pattern Recognition , 2014
2014
Cited alongside, same era.
J. Kuen, K. M. Lim, and C. P. Lee, “Self-taught learning of a deep invariant representation for visual tracking via temporal slowness principle,” Pattern Recognition , vol. 48, no. 10, pp. 2964–2982, 2015
2015
Later among the works it cites.
——, “Robust online visual tracking with a single convolutional neural network,” in Computer Vision–ACCV 2014 . Springer, 2015, pp. 194–209
2015
Later among the works it cites.
2015
Later among the works it cites.
L. Wang, T. Liu, G. Wang, K. L. Chan, and Q. Yang, “Video tracking using learned hierarchical features,” Image Processing, IEEE Transactions on , vol. 24, no. 4, pp. 1424–1435, 2015
2015
Later among the works it cites.
2015
Later among the works it cites.
C. Ma, J.-B. Huang, X. Yang, and M.-H. Yang, “Hierarchical convolutional features for visual tracking,” in Proceedings of the IEEE International Conference on Computer Vision , 2015, pp. 3074–3082
2015
Later among the works it cites.
L. Wang, W. Ouyang, X. Wang, and H. Lu, “Visual tracking with fully convolutional networks,” in Proceedings of the IEEE International Conference on Computer Vision , 2015, pp. 3119–3127
2015
Later among the works it cites.
Y. Qi, S. Zhang, L. Qin, H. Yao, Q. Huang, and J. L. M.-H. Yang, “Hedged deep tracking,” in Proceedings of IEEE Conference on Computer Vision and Pattern Recognition , 2016
2016
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