1. The Seventh Visual Object Tracking VOT2019 Challenge Results
- Author
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Kristan, M., Matas, J., Leonardis, A., Felsberg, M., Pflugfelder, R., Kämäräinen, J.-K., Čehovin Zajc, L., Drbohlav, O., Lukežič, A., Berg, A., Eldesokey, A., Käpylä, J., Fernández, G., Gonzalez-Garcia, A., Memarmoghadam, A., Lu, A., He, A., Varfolomieiev, A., Chan, A., Shekhar Tripathi, A., Smeulders, A., Suraj Pedasingu, B., Chen, B.X., Zhang, B., Wu, B., Li, B., He, B., Yan, B., Bai, B., Kim, B.H., Ma, C., Fang, C., Qian, C., Chen, C., Li, C., Zhang, C., Tsai, C.-Y., Luo, C., Micheloni, C., Tao, D., Gupta, D., Song, D., Wang, D., Gavves, E., Yi, E., Khan, F.S., Zhang, F., Wang, F., Zhao, F., De Ath, G., Bhat, G., Chen, G., Wang, G., Li, G., Cevikalp, H., Du, H., Zhao, H., Saribas, H., Jung, H.M., Bai, H., Hu, H., Peng, H., Lu, H., Li, H., Li, J., Fu, J., Chen, J., Gao, J., Zhao, J., Tang, J., Wu, J., Liu, J., Wang, J., Qi, J., Zhang, J., Tsotsos, J.K., Lee, J.H., van de Weijer, J., Kittler, J., Zhuang, J., Zhang, K., Wang, K., Dai, K., Chen, L., Liu, L., Guo, L., Zhang, L., Wang, L., Zhou, L., Zheng, L., Rout, L., Van Gool, L., Bertinetto, L., Danelljan, M., Dunnhofer, M., Ni, M., Kim, M.Y., Tang, M., Yang, M.-H., Paluru, N., Martinel, N., Xu, P., Zhang, P., Zheng, P., Torr, P.H.S., Zhang, Q., Wang, Q., Guo, Q., Timofte, R., Gorthi, R.K., Everson, R., Han, R., Zhang, R., You, S., Zhao, S.-C., Zhao, S., Li, S., Ge, S., Bai, S., Guan, S., Xing, T., Xu, T., Yang, T., Zhang, T., Vojíř, T., Feng, W., Hu, W., Wang, W., Tang, W., Zeng, W., Liu, W., Chen, X., Qiu, X., Bai, X., Wu, X.-J., Yang, X., Li, X., Sun, X., Tian, X., Tang, X., Zhu, X.-F., Huang, Y., Chen, Y., Lian, Y., Gu, Y., Liu, Y., Zhang, Y., Xu, Y., Wang, Y., Li, Y., Zhou, Y., Dong, Y., Wang, Z., Luo, Z., Zhang, Z., Feng, Z.-H., He, Z., Song, Z., Chen, Z., Wu, Z., Xiong, Z., Huang, Z., Teng, Z., Ni, Z., and Intelligent Sensory Information Systems (IVI, FNWI)
- Subjects
Source code ,Computer science ,business.industry ,media_common.quotation_subject ,Object tracking ,Performance evaluation ,VOT challenge ,020206 networking & telecommunications ,02 engineering and technology ,Visualization ,Datorseende och robotik (autonoma system) ,Robustness (computer science) ,Video tracking ,0202 electrical engineering, electronic engineering, information engineering ,RGB color model ,020201 artificial intelligence & image processing ,Computer vision ,Artificial intelligence ,business ,Computer Vision and Robotics (Autonomous Systems) ,media_common - Abstract
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) VOT-ST2019 challenge focused on short-term tracking in RGB, (ii) VOT-RT2019 challenge focused on "real-time" short-term tracking in RGB, (iii) VOT-LT2019 focused on long-term 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 short-term, 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(1). Funding Agencies|Slovenian research agencySlovenian Research Agency - Slovenia [J2-8175, P2-0214, P2-0094]; Czech Science Foundation Project GACR [P103/12/G084]; MURI project - MoD/DstlMURI; EPSRCEngineering & Physical Sciences Research Council (EPSRC) [EP/N019415/1]; WASP; VR (ELLIIT, LAST, and NCNN); SSF (SymbiCloud); AIT Strategic Research Programme; Faculty of Computer Science, University of Ljubljana, Slovenia
- Published
- 2019