The Visual Object Tracking VOT2017 Challenge Results

Matej Kristan, Ales Leonardis, Jiri Matas, Michael Felsberg, Roman Pflugfelder, Luka Cehovin Zajc, Tomas Vojir, Gustav Hager, Alan Lukezic, Abdelrahman Eldesokey, Gustavo Fernandez, Alvaro Garcia-Martin, A. Muhic, Alfredo Petrosino, Alireza Memarmoghadam, Andrea Vedaldi, Antoine Manzanera, Antoine Tran, Aydin Alatan, Bogdan MocanuBoyu Chen, Chang Huang, Changsheng Xu, Chong Sun, Dalong Du, David Zhang, Dawei Du, Deepak Mishra, Erhan Gundogdu, Erik Velasco-Salido, Fahad Shahbaz Khan, Francesco Battistone, Gorthi R. K. Sai Subrahmanyam, Goutam Bhat, Guan Huang, Guilherme Bastos, Guna Seetharaman, Hongliang Zhang, Houqiang Li, Huchuan Lu, Isabela Drummond, Jack Valmadre, Jae-chan Jeong, Jae-il Cho, Jae-Yeong Lee, Jana Noskova, Jianke Zhu, Jin Gao, Jingyu Liu, Ji-Wan Kim, Joao F. Henriques, Jose M. Martinez, Junfei Zhuang, Junliang Xing, Junyu Gao, Kai Chen, Kannappan Palaniappan, Karel Lebeda, Ke Gao, Kris M. Kitani, Lei Zhang, Lijun Wang, Lingxiao Yang, Longyin Wen, Luca Bertinetto, Mahdieh Poostchi, Martin Danelljan, Matthias Müller, Mengdan Zhang, Ming-Hsuan Yang, Nianhao Xie, Ning Wang, Ondrej Miksik, P. Moallem, Pallavi Venugopal M, Pedro Senna, Philip H. S. Torr, Qiang Wang, Qifeng Yu, Qingming Huang, Rafael Martin-Nieto, Richard Bowden, Risheng Liu, Ruxandra Tapu, Simon Hadfield, Siwei Lyu, Stuart Golodetz, Sunglok Choi, Tianzhu Zhang, Titus Zaharia, Vincenzo Santopietro, Wei Zou, Weiming Hu, Wenbing Tao, Wenbo Li, Wengang Zhou, Xianguo Yu, Xiao Bian, Yang Li, Yifan Xing, Yingruo Fan, Zheng Zhu, Zhipeng Zhang, Zhiqun He

Research output: Chapter in Book/Report/Conference proceedingConference contribution

440 Scopus citations


The Visual Object Tracking challenge VOT2017 is the fifth annual tracker benchmarking activity organized by the VOT initiative. Results of 51 trackers are presented; many are state-of-the-art published at major computer vision conferences or journals in recent years. The evaluation included the standard VOT and other popular methodologies and a new 'real-time' experiment simulating a situation where a tracker processes images as if provided by a continuously running sensor. Performance of the tested trackers typically by far exceeds standard baselines. The source code for most of the trackers is publicly available from the VOT page. The VOT2017 goes beyond its predecessors by (i) improving the VOT public dataset and introducing a separate VOT2017 sequestered dataset, (ii) introducing a realtime tracking experiment and (iii) releasing a redesigned toolkit that supports complex experiments. The dataset, the evaluation kit and the results are publicly available at the challenge website1.
Original languageEnglish (US)
Title of host publication2017 IEEE International Conference on Computer Vision Workshops (ICCVW)
PublisherInstitute of Electrical and Electronics Engineers (IEEE)
Number of pages24
ISBN (Print)9781538610343
StatePublished - Jan 22 2018

Bibliographical note

KAUST Repository Item: Exported on 2020-10-01
Acknowledgements: This work was supported in part by the following research programs and projects: Slovenian research agency research programs P2-0214, P2-0094, Slovenian research agency project J2–8175. Jifi Matas and Tomáš Vojíř were supported by the Czech Science Foundation Project GACR P103/12/G084. Michael Felsberg and Gustav Häger were supported by WASP, VR (EMC2), SSF (SymbiCloud), and SNIC. Gustavo Fernández and Roman Pflugfelder were supported by the AIT Strategic Research Programme 2017 Visual Surveillance and Insight. The challenge was sponsored by Faculty of Computer Science, University of Ljubljana, Slovenia.


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