Details

Autor(en) / Beteiligte

• Kristan, Matej
• Matas, Jiri
• Felsberg, Michael
• Kamarainen, Joni-Kristian
• Drbohlav, Ondrej
• Kapyla, Jani
• Fernandez, Gustavo
• Memarmoghadam, Alireza
• He, Anfeng
• Varfolomieiev, Anton
• Chan, Antoni
• Tripathi, Ardhendu Shekhar
• Smeulders, Arnold
• Zhang, Baopeng
• He, Bin
• Yan, Bin
• Ma, Chao
• Fang, Chen
• Zhang, Chengquan
• Tsai, Chi-Yi
• Luo, Chong
• Micheloni, Christian
• Zhang, Chunhui
• Gupta, Deepak
• Song, Dejia
• Yi, Eunu
• Khan, Fahad Shahbaz
• Zhang, Fangyi
• Bhat, Goutam
• Chen, Guangqi
• Wang, Guangting
• Li, Guoxuan
• Cevikalp, Hakan
• Zhao, Haojie
• Saribas, Hasan
• Yu, Hongyuan
• Lu, Huchuan
• Li, Hui
• Chen, Jie
• Gao, Jie
• Tang, Jin
• Wu, Jingjing
• Liu, Jingtuo
• Qi, Jinqing
• Lee, Jong Hyuk
• Weijer, Joost van de
• Kittler, Josef
• Lee, Jun Ha
• Wang, Kangkang
• Dai, Kenan
• Liu, Lei
• Wang, Liang
• Wang, Liangliang
• Zhang, Lichao
• Gool, Luc Van
• Bertinetto, Luca
• Danelljan, Martin
• Dunnhofer, Matteo
• Ni, Meng
• Kim, Min Young
• Tang, Ming
• Paluru, Naveen
• Martinel, Niki
• Zhang, Pengfei
• Zheng, Pengkun
• Zhang, Pengyu
• Wang, Qi Zhang Qiang
• Everson, Richard
• Han, Ruize
• Zhang, Ruohan
• You, Shan
• Zhao, Shao-Chuan
• Zhao, Shengwei
• Li, Shihu
• Ge, Shiming
• Bai, Shuai
• Guan, Shuosen
• Xing, Tengfei
• Yang, Tianyu
• Zhang, Ting
• Feng, Wei
• Hu, Weiming
• Wang, Weizhao
• Liu, Wenyu
• Qiu, Xi
• Chen, Xingyu
• Tang, Xu
• Huang, Yan
• Chen, Yanan
• Lian, Yanchao
• Gu, Yang
• Liu, Yang
• Xu, Yinda
• Zhou, Yu
• Zhang, Yunhua
• Li, Yunkun
• Luo, Zeyu Wang Zhao
• Chen, Zhihao
• Xiong, Zhiwei
• Teng, Zhu

Titel

The Seventh Visual Object Tracking VOT2019 Challenge Results

Ist Teil von

• 2019 IEEE/CVF International Conference on Computer Vision Workshop (ICCVW), 2019, p.2206-2241

Ort / Verlag

IEEE

Erscheinungsjahr

2019

Link zum Volltext

• IEEE_Xplore

Quelle

IEEE Electronic Library (IEL)

Beschreibungen/Notizen

• The Visual Object Tracking challenge VOT2019 is the seventh annual tracker benchmarking activity organized by the VOT initiative. Results of 81 trackers are presented; many are state-of-the-art trackers published at major computer vision conferences or in journals in the recent years. The evaluation included the standard VOT and other popular methodologies for short-term tracking analysis as well as the standard VOT methodology for long-term tracking analysis. The VOT2019 challenge was composed of five challenges focusing on different tracking domains: (i) VOTST2019 challenge focused on short-term tracking in RGB, (ii) VOT-RT2019 challenge focused on "real-time" shortterm tracking in RGB, (iii) VOT-LT2019 focused on longterm tracking namely coping with target disappearance and reappearance. Two new challenges have been introduced: (iv) VOT-RGBT2019 challenge focused on short-term tracking in RGB and thermal imagery and (v) VOT-RGBD2019 challenge focused on long-term tracking in RGB and depth imagery. The VOT-ST2019, VOT-RT2019 and VOT-LT2019 datasets were refreshed while new datasets were introduced for VOT-RGBT2019 and VOT-RGBD2019. The VOT toolkit has been updated to support both standard shortterm, long-term tracking and tracking with multi-channel imagery. 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 dataset, the evaluation kit and the results are publicly available at the challenge website.