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We propose FuCoLoT -- a Fully Correlational Long-term Tracker.
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van de Weijer, J., Schmid, C., Verbeek, J., Larlus, D.: Learning color names for real-world applications. IEEE Trans. Image Proc. 18
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Chang, H.J., Park, M.S., Jeong, H., Choi, J.Y.: Tracking failure detection by imitating human visual perception. In: Proc. Int. Conf. Image Processing. pp. 3293–3296 (2011)
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Kwak, S., Nam, W., Han, B., Han, J.H.: Learning occlusion with likelihoods for visual tracking. In: Int. Conf. Computer Vision. pp. 1551–1558 (2011)
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Kalal, Z., Mikolajczyk, K., Matas, J.: Tracking-learning-detection. IEEE Trans. Pattern Anal. Mach. Intell. 34
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Galoogahi, H.K., Sim, T., Lucey, S.: Multi-channel correlation filters. In: Int. Conf. Computer Vision. pp. 3072–3079 (2013)
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Maresca, M.E., Petrosino, A.: Matrioska: A multi-level approach to fast tracking by learning. In: Proc. Int. Conf. Image Analysis and Processing. pp. 419–428 (2013)
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Pernici, F., Del Bimbo, A.: Object tracking by oversampling local features. IEEE Trans. Pattern Anal. Mach. Intell. 36
2013
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Danelljan, M., Khan, F.S., Felsberg, M., van de Weijer, J.: Adaptive color attributes for real-time visual tracking. pp. 1090–1097 (2014)
2014
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Kristan, M., Perš, J., Sulič, V., Kovačič, S.: A graphical model for rapid obstacle image-map estimation from unmanned surface vehicles. In: Proc. Asian Conf. Computer Vision. pp. 391–406 (2014)
2014
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Li, Y., Zhu, J.: A scale adaptive kernel correlation filter tracker with feature integration. In: Proc. European Conf. Computer Vision. pp. 254–265 (2014)
2014
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Danelljan, M., Hager, G., Shahbaz Khan, F., Felsberg, M.: Learning spatially regularized correlation filters for visual tracking. In: Int. Conf. Computer Vision. pp. 4310–4318 (2015)
2015
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Henriques, J.F., Caseiro, R., Martins, P., Batista, J.: High-speed tracking with kernelized correlation filters. IEEE Trans. Pattern Anal. Mach. Intell. 37
2015
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Hong, Z., Chen, Z., Wang, C., Mei, X., Prokhorov, D., Tao, D.: Multi-store tracker (muster): A cognitive psychology inspired approach to object tracking. In: Comp. Vis. Patt. Recognition. pp. 749–758 (June 2015)
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Kiani Galoogahi, H., Sim, T., Lucey, S.: Correlation filters with limited boundaries. In: Comp. Vis. Patt. Recognition. pp. 4630–4638 (2015)
2015
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Mueller, M., Smith, N., Ghanem, B.: A benchmark and simulator for uav tracking. In: Proc. European Conf. Computer Vision. pp. 445–461 (2016)
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Nam, H., Han, B.: Learning multi-domain convolutional neural networks for visual tracking. In: Comp. Vis. Patt. Recognition. pp. 4293–4302 (June 2016)
2016
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Tao, R., Gavves, E., Smeulders, A.W.M.: Siamese instance search for tracking. In: Comp. Vis. Patt. Recognition. pp. 1420–1429 (2016)
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2017
Closest in time.
Chi, Z., Li, H., Lu, H., Yang, M.H.: Dual deep network for visual tracking. IEEE Trans. Image Proc. 26
2017
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Kristan, M., Matas, J., Leonardis, A., Felsberg, M., Čehovin, L., Fernandez, G., Vojir, T., Häger, G., Nebehay, G., et al. Pflugfelder, R.: The visual object tracking vot2015 challenge results. In: Int. Conf. Computer Vision (2015)
2015
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Ma, C., Yang, X., Zhang, C., Yang, M.H.: Long-term correlation tracking. In: Comp. Vis. Patt. Recognition. pp. 5388–5396 (2015)
2015
Cited alongside, same era.
Nebehay, G., Pflugfelder, R.: Clustering of static-adaptive correspondences for deformable object tracking. In: Comp. Vis. Patt. Recognition. pp. 2784–2791 (2015)
2015
Cited alongside, same era.
Wang, L., Ouyang, W., Wang, X., Lu, H.: Visual tracking with fully convolutional networks. In: Int. Conf. Computer Vision. pp. 3119–3127 (Dec 2015)
2015
Cited alongside, same era.
Wu, Y., Lim, J., Yang, M.H.: Object tracking benchmark. IEEE Trans. Pattern Anal. Mach. Intell. 37
2015
Cited alongside, same era.
Bertinetto, L., Valmadre, J., Henriques, J.F., Vedaldi, A., Torr, P.H.: Fully-convolutional siamese networks for object tracking (2016)
2016
Cited alongside, same era.
Danelljan, M., Robinson, A., Khan, F.S., Felsberg, M.: Beyond correlation filters: learning continuous convolution operators for visual tracking. In: Proc. European Conf. Computer Vision. pp. 472–488 (2016)
2016
Cited alongside, same era.
Kristan, M., Matas, J., Leonardis, A., Vojir, T., Pflugfelder, R., Fernandez, G., Nebehay, G., Porikli, F., Cehovin, L.: A novel performance evaluation methodology for single-target trackers. IEEE Trans. Pattern Anal. Mach. Intell. (2016)
2016
Cited alongside, same era.
Closest in time.
Danelljan, M., Häger, G., Khan, F.S., Felsberg, M.: Discriminative scale space tracking. IEEE Trans. Pattern Anal. Mach. Intell. 39
2017
Closest in time.
Danelljan, M., Bhat, G., Shahbaz Khan, F., Felsberg, M.: Eco: Efficient convolution operators for tracking. In: Comp. Vis. Patt. Recognition. pp. 6638–6646 (2017)
2017
Closest in time.
Du, D., Qi, H., Wen, L., Tian, Q., Huang, Q., Lyu, S.: Geometric hypergraph learning for visual tracking. IEEE Trans. on Cyber. 47
2017
Closest in time.
Fan, H., Ling, H.: Parallel tracking and verifying: A framework for real-time and high accuracy visual tracking. In: Int. Conf. Computer Vision. pp. 5486–5494 (2017)
2017
Closest in time.
Lukežič, A., Vojíř, T., Čehovin Zajc, L., Matas, J., Kristan, M.: Discriminative correlation filter with channel and spatial reliability. In: Comp. Vis. Patt. Recognition. pp. 6309–6318 (2017)
2017
Closest in time.
Valmadre, J., Bertinetto, L., Henriques, J., Vedaldi, A., Torr, P.H.S.: End-to-end representation learning for correlation filter based tracking. In: Comp. Vis. Patt. Recognition. pp. 2805–2813 (2017)
2017
Closest in time.
Du, D., Wen, L., Qi, H., Huang, Q., Tian, Q., Lyu, S.: Iterative graph seeking for object tracking. IEEE Trans. Image Proc. 27
2018
Closest in time.
Ma, C., Huang, J.B., Yang, X., Yang, M.H.: Adaptive correlation filters with long-term and short-term memory for object tracking. Int. J. Comput. Vision 126
2018
Closest in time.