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Human following on mobile robots has witnessed significant advances due to its potentials for real-world applications.
L. Dressel and M. J. Kochenderfer, “Hunting drones with other drones: Tracking a moving radio target,” in
1912
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M. Kobilarov, G. Sukhatme, J. Hyams, and P. Batavia, “People tracking and following with mobile robot using an omnidirectional camera and a laser,” in
2006
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N. Bellotto and H. Hu, “Multisensor-based human detection and tracking for mobile service robots,”
2009
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A. Krizhevsky, I. Sutskever, and G. E. Hinton, “Imagenet classification with deep convolutional neural networks,” in
2012
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Y. Wu, J. Lim, and M. H. Yang, “Online object tracking: A benchmark,” in
2013
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N. Wang and D.-Y. Yeung, “Learning a deep compact image representation for visual tracking,” in
2013
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Y. Taigman, M. Yang, M. Ranzato, and L. Wolf, “Deepface: Closing the gap to human-level performance in face verification,” in
2014
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A. V. Gulalkari, G. Hoang, P. S. Pratama, H. K. Kim, S. B. Kim, and B. H. Jun, “Object following control of six-legged robot using kinect camera,” in
2014
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N. Hirose, R. Tajima, and K. Sukigara, “Personal robot assisting transportation to support active human life—human-following method based on model predictive control for adjacency without collision,” in
2015
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Y. Wu and J. Lim, “Object tracking benchmark,”
2015
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F. Schroff, D. Kalenichenko, and J. Philbin, “Facenet: A unified embedding for face recognition and clustering,” in
2015
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S. Ren, K. He, R. Girshick, and J. Sun, “Faster r-cnn: towards real-time object detection with region proposal networks,” in
2015
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M. Danelljan, G. Hager, F. S. Khan, and M. Felsberg, “Convolutional features for correlation filter based visual tracking,” in
2015
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C. Ma, J.-B. Huang, X. Yang, and M.-H. Yang, “Hierarchical convolutional features for visual tracking,” in
2015
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A. V. Gulalkari, P. S. Pratama, G. Hoang, D. H. Kim, B. H. Jun, and S. B. Kim, “Object tracking and following six-legged robot system using kinect camera based on kalman filter and backstepping controller,”
2015
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A. Dosovitskiy, P. Fischer, E. Ilg, P. Hausser, C. Hazirbas, V. Golkov, P. van der Smagt, D. Cremers, and T. Brox, “Flownet: Learning optical flow with convolutional networks,” in
2015
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K. He, X. Zhang, S. Ren, and J. Sun, “Deep residual learning for image recognition,” in
2016
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H. Li, Y. Li, and F. Porikli, “Deeptrack: Learning discriminative feature representations online for robust visual tracking,”
2016
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Y. Qi, S. Zhang, L. Qin, H. Yao, Q. Huang, J. Lim, and M.-H. Yang, “Hedged deep tracking,” in
2016
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H. Nam and B. Han, “Learning multi-domain convolutional neural networks for visual tracking,” in
2016
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M. Danelljan, A. Robinson, F. S. Khan, and M. Felsberg, “Beyond correlation filters: Learning continuous convolution operators for visual tracking,” in
2016
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L. Bertinetto, J. Valmadre, J. F. Henriques, A. Vedaldi, and P. H. S. Torr, “Fully-convolutional siamese networks for object tracking,” in
2016
Cited alongside, same era.
Z. Zhu, W. Zou, Q. Wang, and F. Zhang, “Std: A stereo tracking dataset for evaluating binocular tracking algorithms,” in
2016
Cited alongside, same era.
A. Mohamed, C. Yang, and A. Cangelosi, “Stereo vision based object tracking control for a movable robot head,”
2016
Cited alongside, same era.
J. Redmon, S. Divvala, R. Girshick, and A. Farhadi, “You only look once: Unified, real-time object detection,” in
2016
Cited alongside, same era.
R. Tao, E. Gavves, and A. W. M. Smeulders, “Siamese instance search for tracking,” in
2016
Cited alongside, same era.
2018
Later among the works it cites.
C. Wang, H. K. Galoogahi, C.-H. Lin, and S. Lucey, “Deep-lk for efficient adaptive object tracking,” in
2018
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Y. Song, C. Ma, X. Wu, L. Gong, L. Bao, W. Zuo, C. Shen, L. Rynson, and M.-H. Yang, “Vital: Visual tracking via adversarial learning,” in
2018
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Z. Zhu, W. Wu, W. Zou, and J. Yan, “End-to-end flow correlation tracking with spatial-temporal attention,” in
2018
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B. Li, W. Wu, Z. Zhu, and J. Yan, “High performance visual tracking with siamese region proposal network,” in
2018
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D. Held, S. Thrun, and S. Savarese, “Learning to track at 100 fps with deep regression networks,” in
2016
Cited alongside, same era.
Q. Wang, W. Zou, D. Xu, and Z. Zhu, “Motion control in saccade and smooth pursuit for bionic eye based on three-dimensional coordinates,”
2017
Cited alongside, same era.
N. Yao, E. Anaya, Q. Tao, S. Cho, H. Zheng, and F. Zhang, “Monocular vision-based human following on miniature robotic blimp,” in
2017
Cited alongside, same era.
M. Kristan, A. Leonardis, J. Matas, M. Felsberg, R. Pflugfelder, L. Cehovin Zajc, T. Vojir, G. Hager, A. Lukezic, A. Eldesokey, and G. Fernandez, “The visual object tracking vot2017 challenge results,” in
2017
Cited alongside, same era.
T. Y. Lin, P. Dollár, R. Girshick, K. He, B. Hariharan, and S. Belongie, “Feature pyramid networks for object detection,” in
2017
Cited alongside, same era.
J. Valmadre, L. Bertinetto, J. F. Henriques, A. Vedaldi, and P. H. S. Torr, “End-to-end representation learning for correlation filter based tracking,” in
2017
Cited alongside, same era.
Y. Song, C. Ma, L. Gong, J. Zhang, R. Lau, and M. H. Yang, “Crest: Convolutional residual learning for visual tracking,” in
2017
Cited alongside, same era.
Z. Zhu, Q. Wang, B. Li, W. Wu, J. Yan, and W. Hu, “Distractor-aware siamese networks for visual object tracking,” in
2018
Later among the works it cites.
2018
Later among the works it cites.
2018
Later among the works it cites.
2018
Later among the works it cites.
Z. Zhu, W. Zou, Q. Wang, and F. Zhang, “A velocity compensation visual servo method for oculomotor control of bionic eyes,”
2018
Later among the works it cites.
M. Wang, Y. Liu, D. Su, Y. Liao, L. Shi, and J. Xu, “Accurate and real-time 3d tracking for the following robots by fusing vision and ultra-sonar information,”
2018
Later among the works it cites.
W. Luo, P. Sun, F. Zhong, W. Liu, T. Zhang, and Y. Wang, “End-to-end active object tracking and its real-world deployment via reinforcement learning,”
2019
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R. Zhang, Z. Zhu, P. Li, R. Wu, C. Guo, G. Huang, and H. Xia, “Exploiting offset-guided network for pose estimation and tracking,” in
2019
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P. Li, J. Zhang, Z. Zhu, Y. Li, L. Jiang, and G. Huang, “State-aware re-identification feature for multi-target multi-camera tracking,” in
2019
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A. Bajcsy, S. L. Herbert, D. Fridovich-Keil, J. F. Fisac, S. Deglurkar, A. D. Dragan, and C. J. Tomlin, “A scalable framework for real-time multi-robot, multi-human collision avoidance,” in
2019
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Z. Kang, W. Zou, H. Ma, and Z. Zhu, “Adaptive trajectory tracking of wheeled mobile robots based on a fish-eye camera,”
2019
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Y. Li, X. Chen, Z. Zhu, L. Xie, G. Huang, D. Du, and X. Wang, “Attention-guided unified network for panoptic segmentation,” in
2019
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2019
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J. Zhu, W. Zou, Z. Zhu, and Y. Hu, “Convolutional relation network for skeleton-based action recognition,”
2019
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J. Razlaw, J. Quenzel, and S. Behnke, “Detection and tracking of small objects in sparse 3d laser range data,” in
2019
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A. Buyval, A. Gabdullin, R. Mustafin, and I. Shimchik, “Realtime vehicle and pedestrian tracking for didi udacity self-driving car challenge,” in
2069
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