Type
Conference PaperAuthors
Kristan, MatejLeonardis, Aleš
Matas, Jiři
Felsberg, Michael
Pflugfelder, Roman
Čehovin, Luka
Vojír̃, Tomáš
Häger, Gustav
Lukežič, Alan
Fernández, Gustavo
Gupta, Abhinav
Petrosino, Alfredo
Memarmoghadam, Alireza
Garcia-Martin, Alvaro
Solís Montero, Andrés
Vedaldi, Andrea
Robinson, Andreas
Ma, Andy J.
Varfolomieiev, Anton
Alatan, Aydin
Erdem, Aykut
Ghanem, Bernard

Liu, Bin
Han, Bohyung
Martinez, Brais
Chang, Chang-Ming
Xu, Changsheng
Sun, Chong
Kim, Daijin
Chen, Dapeng
Du, Dawei
Mishra, Deepak
Yeung, Dit-Yan
Gundogdu, Erhan
Erdem, Erkut
Khan, Fahad
Porikli, Fatih
Zhao, Fei
Bunyak, Filiz
Battistone, Francesco
Zhu, Gao
Roffo, Giorgio
Subrahmanyam, Gorthi R. K. Sai
Bastos, Guilherme
Seetharaman, Guna
Medeiros, Henry
Li, Hongdong
Qi, Honggang
Bischof, Horst
Possegger, Horst
Lu, Huchuan
Lee, Hyemin
Nam, Hyeonseob
Chang, Hyung Jin
Drummond, Isabela
Valmadre, Jack
Jeong, Jae-chan
Cho, Jae-il
Lee, Jae-Yeong
Zhu, Jianke
Feng, Jiayi
Gao, Jin
Choi, Jin Young
Xiao, Jingjing
Kim, Ji-Wan
Jeong, Jiyeoup
Henriques, João F.
Lang, Jochen
Choi, Jongwon
Martinez, Jose M.
Xing, Junliang
Gao, Junyu
Palaniappan, Kannappan
Lebeda, Karel
Gao, Ke
Mikolajczyk, Krystian
Qin, Lei
Wang, Lijun
Wen, Longyin
Bertinetto, Luca
Rapuru, Madan Kumar
Poostchi, Mahdieh
Maresca, Mario
Danelljan, Martin
Mueller, Matthias

Zhang, Mengdan
Arens, Michael
Valstar, Michel
Tang, Ming
Baek, Mooyeol
Khan, Muhammad Haris
Wang, Naiyan
Fan, Nana
Al-Shakarji, Noor
Miksik, Ondrej
Akin, Osman
Moallem, Payman
Senna, Pedro
Torr, Philip H. S.
Yuen, Pong C.
Huang, Qingming
Martin-Nieto, Rafael
Pelapur, Rengarajan
Bowden, Richard
Laganière, Robert
Stolkin, Rustam
Walsh, Ryan
Krah, Sebastian B.
Li, Shengkun
Zhang, Shengping
Yao, Shizeng
Hadfield, Simon
Melzi, Simone
Lyu, Siwei
Li, Siyi
Becker, Stefan
Golodetz, Stuart
Kakanuru, Sumithra
Choi, Sunglok
Hu, Tao
Mauthner, Thomas
Zhang, Tianzhu
Pridmore, Tony
Santopietro, Vincenzo
Hu, Weiming
Li, Wenbo
Hübner, Wolfgang
Lan, Xiangyuan
Wang, Xiaomeng
Li, Xin

Li, Yang
Demiris, Yiannis
Wang, Yifan
Qi, Yuankai
Yuan, Zejian
Cai, Zexiong
Xu, Zhan
He, Zhenyu
Chi, Zhizhen
KAUST Department
Computer, Electrical and Mathematical Sciences and Engineering (CEMSE) DivisionElectrical Engineering Program
Visual Computing Center (VCC)
Date
2016-11-02Online Publication Date
2016-11-03Print Publication Date
2016Embargo End Date
2017-11-02Permanent link to this record
http://hdl.handle.net/10754/622260
Metadata
Show full item recordAbstract
The Visual Object Tracking challenge VOT2016 aims at comparing short-term single-object visual trackers that do not apply pre-learned models of object appearance. Results of 70 trackers are presented, with a large number of trackers being published at major computer vision conferences and journals in the recent years. The number of tested state-of-the-art trackers makes the VOT 2016 the largest and most challenging benchmark on short-term tracking to date. For each participating tracker, a short description is provided in the Appendix. The VOT2016 goes beyond its predecessors by (i) introducing a new semi-automatic ground truth bounding box annotation methodology and (ii) extending the evaluation system with the no-reset experiment. The dataset, the evaluation kit as well as the results are publicly available at the challenge website (http://votchallenge.net).Citation
Kristan M, Leonardis A, Matas J, Felsberg M, Pflugfelder R, et al. (2016) The Visual Object Tracking VOT2016 Challenge Results. Computer Vision – ECCV 2016 Workshops: 777–823. Available: http://dx.doi.org/10.1007/978-3-319-48881-3_54.Sponsors
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 projects J2-4284, J2-3607, J2-2221 and European Union seventh framework programme under grant agreement no 257906. Jiři Matas and Tomáš Vojíř were supported by CTU Project SGS13/142/OHK3/2T/13 and by the Technology Agency of the Czech Republic project TE01020415 (V3C – Visual Computing Competence Center). Michael Felsberg and Gustav Häger were supported by the Wallenberg Autonomous Systems Program WASP, the Swedish Foundation for Strategic Research through the project CUAS, and the Swedish Research Council trough the project EMC2. Gustavo Fernández and Roman Pflugfelder were supported by the research program Mobile Vision with funding from the Austrian Institute of Technology. Some experiments where run on GPUs donated by NVIDIA.Publisher
Springer NatureConference/Event name
14th European Conference on Computer Vision, ECCV 2016Additional Links
http://link.springer.com/chapter/10.1007%2F978-3-319-48881-3_54https://repository.kaust.edu.sa/bitstream/10754/605657/1/Kristan_The_Visual_Object_ICCV_2015_paper.pdf
ae974a485f413a2113503eed53cd6c53
10.1007/978-3-319-48881-3_54