The Ninth Visual Object Tracking VOT2021 Challenge Results

Matej Kristan, University of Ljubljana, Slovenia
Jiri Matas, Czech Technical University, Czech Republic
Ales Leonardis, University of Birmingham, United Kingdom
Michael Felsberg, Link oping University, Sweden
Roman Pflugfelder, Austrian Institute of Technology, Austria & TU Wien, Austria
Joni-Kristian Kamarainen, Tampere University, Finland
Hyung Jin Chang, University of Birmingham, United Kingdom
Martin Danelljan, ETH Zurich, Switzerland
Luka Cehovin Zajc, University of Ljubljana, Slovenia
Alan Lukezic, University of Ljubljana, Slovenia
Ondrej Drbohlav, Czech Technical University, Czech Republic
Jani Kapyla, Tampere University, Finland


The Visual Object Tracking challenge VOT2021 is the ninth annual tracker benchmarking activity organized by the VOT initiative. Results of 71 trackers are presented; many are state-of-the-art trackers published at major computer vision conferences or in journals in recent years. The VOT2021 challenge was composed of four sub-challenges focusing on different tracking domains: (i) VOT-ST2021 challenge focused on short-term tracking in RGB, (ii) VOT-RT2021 challenge focused on "real-time"short-term tracking in RGB, (iii) VOT-LT2021 focused on long-term tracking, namely coping with target disappearance and reappearance and (iv) VOT-RGBD2021 challenge focused on long-term tracking in RGB and depth imagery. The VOT-ST2021 dataset was refreshed, while VOT-RGBD2021 introduces a training dataset and sequestered dataset for winner identification. The source code for most of the trackers, the datasets, the evaluation kit and the results along with the source code for most trackers are publicly available at the challenge website1. © 2021 IEEE.