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We propose a new long video dataset (called Track Long and Prosper - TLP) and benchmark for single object tracking.
Dalal, N., Triggs, B.: Histograms of oriented gradients for human detection. In: CVPR (2005)
2005
Earlier work this paper cites.
Grabner, H., Leistner, C., Bischof, H.: Semi-supervised on-line boosting for robust tracking. ECCV (2008)
2008
Earlier work this paper cites.
Bolme, D.S., Beveridge, J.R., Draper, B.A., Lui, Y.M.: Visual object tracking using adaptive correlation filters. In: CVPR (2010)
2010
Earlier work this paper cites.
Babenko, B., Yang, M.H., Belongie, S.: Robust object tracking with online multiple instance learning. IEEE transactions on pattern analysis and machine intelligence 33
2011
Earlier work this paper cites.
Grundmann, M., Kwatra, V., Essa, I.: Auto-directed video stabilization with robust l1 optimal camera paths. In: CVPR (2011)
2011
Earlier work this paper cites.
Henriques, J.F., Caseiro, R., Martins, P., Batista, J.: Exploiting the circulant structure of tracking-by-detection with kernels. In: ECCV (2012)
2012
Earlier work this paper cites.
Kalal, Z., Mikolajczyk, K., Matas, J.: Tracking-learning-detection. IEEE transactions on pattern analysis and machine intelligence 34
2012
Earlier work this paper cites.
Vondrick, C., Patterson, D., Ramanan, D.: Efficiently scaling up crowdsourced video annotation. IJCV pp. 1–21 (2012)
2012
Earlier work this paper cites.
Lu, W.L., Ting, J.A., Little, J.J., Murphy, K.P.: Learning to track and identify players from broadcast sports videos. IEEE transactions on pattern analysis and machine intelligence 35
2013
Earlier work this paper cites.
Supancic, J.S., Ramanan, D.: Self-paced learning for long-term tracking. In: CVPR (2013)
2013
Earlier work this paper cites.
Wang, N., Yeung, D.Y.: Learning a deep compact image representation for visual tracking. In: NIPS. pp. 809–817 (2013)
2013
Earlier work this paper cites.
Wu, Y., Lim, J., Yang, M.H.: Online object tracking: A benchmark. In: CVPR (2013)
2013
Earlier work this paper cites.
Danelljan, M., Häger, G., Khan, F., Felsberg, M.: Accurate scale estimation for robust visual tracking. In: BMVC (2014)
2014
Earlier work this paper cites.
Danelljan, M., Shahbaz Khan, F., Felsberg, M., Van de Weijer, J.: Adaptive color attributes for real-time visual tracking. In: CVPR (2014)
2014
Earlier work this paper cites.
Hua, Y., Alahari, K., Schmid, C.: Occlusion and motion reasoning for long-term tracking. In: ECCV (2014)
2014
Earlier work this paper cites.
Kristan, M., Matas, J., Leonardis, A., et al.: The visual object tracking vot2014 challenge results. In: ECCV Workshop (2014)
2014
Earlier work this paper cites.
Li, H., Li, Y., Porikli, F.: Robust online visual tracking with a single convolutional neural network. In: ACCV (2014)
2014
Cited alongside, same era.
Li, Y., Zhu, J.: A scale adaptive kernel correlation filter tracker with feature integration. In: ECCV Workshops (2). pp. 254–265 (2014)
2014
Cited alongside, same era.
Smeulders, A.W., Chu, D.M., Cucchiara, R., Calderara, S., Dehghan, A., Shah, M.: Visual tracking: An experimental survey. TPAMI 36
2014
Cited alongside, same era.
Zhang, J., Ma, S., Sclaroff, S.: Meem: robust tracking via multiple experts using entropy minimization. In: ECCV (2014)
2014
Cited alongside, same era.
Danelljan, M., Hager, G., Shahbaz Khan, F., Felsberg, M.: Learning spatially regularized correlation filters for visual tracking. In: ICCV (2015)
2015
Cited alongside, same era.
2016
Later among the works it cites.
Danelljan, M., Robinson, A., Shahbaz Khan, F., Felsberg, M.: Beyond correlation filters: Learning continuous convolution operators for visual tracking. In: ECCV (2016)
2016
Later among the works it cites.
Held, D., Thrun, S., Savarese, S.: Learning to track at 100 fps with deep regression networks. In: ECCV (2016)
2016
Later among the works it cites.
Mueller, M., Smith, N., Ghanem, B.: A benchmark and simulator for uav tracking. In: ECCV (2016)
2016
Later among the works it cites.
Nam, H., Han, B.: Learning multi-domain convolutional neural networks for visual tracking. In: CVPR (2016)
2016
Later among the works it cites.
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Henriques, J.F., Caseiro, R., Martins, P., Batista, J.: High-speed tracking with kernelized correlation filters. TPAMI 37
2015
Cited alongside, same era.
Hong, S., You, T., Kwak, S., Han, B.: Online tracking by learning discriminative saliency map with convolutional neural network. In: ICML (2015)
2015
Cited alongside, same era.
Kiani Galoogahi, H., Sim, T., Lucey, S.: Correlation filters with limited boundaries. In: CVPR (2015)
2015
Cited alongside, same era.
Kristan, M., Matas, J., Leonardis, A., Felsberg, M., Cehovin, L., Fernández, G., Vojir, T., Hager, G., Nebehay, G., Pflugfelder, R.: The visual object tracking vot2015 challenge results. In: ICCV workshops. pp. 1–23 (2015)
2015
Cited alongside, same era.
Liang, P., Blasch, E., Ling, H.: Encoding color information for visual tracking: Algorithms and benchmark. IEEE Transactions on Image Processing 24
2015
Cited alongside, same era.
Ma, C., Huang, J.B., Yang, X., Yang, M.H.: Hierarchical convolutional features for visual tracking. In: ICCV (2015)
2015
Cited alongside, same era.
Ma, C., Yang, X., Zhang, C., Yang, M.H.: Long-term correlation tracking. In: CVPR (2015)
2015
Cited alongside, same era.
Danelljan, M., Bhat, G., Shahbaz Khan, F., Felsberg, M.: Eco: Efficient convolution operators for tracking. In: CVPR (2017)
2017
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2017
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Kiani Galoogahi, H., Fagg, A., Lucey, S.: Learning background-aware correlation filters for visual tracking. In: CVPR (2017)
2017
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Kumar, M., Gandhi, V., Ronfard, R., Gleicher, M.: Zooming on all actors: Automatic focus+ context split screen video generation. In: Computer Graphics Forum. vol. 36, pp. 455–465. Wiley Online Library (2017)
2017
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Song, Y., Ma, C., Gong, L., Zhang, J., Lau, R., Yang, M.H.: Crest: Convolutional residual learning for visual tracking. In: ICCV (2017)
2017
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Yun, S., Choi, J., Yoo, Y., Yun, K., Young Choi, J.: Action-decision networks for visual tracking with deep reinforcement learning. In: CVPR (2017)
2017
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Zhang, T., Xu, C., Yang, M.H.: Multi-task correlation particle filter for robust object tracking. In: CVPR (2017)
2017
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ˇCehovin Zajc, L., Lukezic, A., Leonardis, A., Kristan, M.: Beyond standard benchmarks: Parameterizing performance evaluation in visual object tracking (2017)
2017
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2018
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