VisDrone-MOT2021: The vision meets drone multiple object tracking challenge results
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info:eu-repo/semantics/embargoedAccessTarih
2021Yazar
Chen, GuanlinWang, Wenguan
He, Zhijian
Wang, Lujia
Yuan, Yixuan
Zhang, Dingwen
Zhang, Jinglin
Zhu, Pengfei
Gool, Luc Van
Han, Junwei
Hoi, Steven
Hu, Qinghua
Liu, Ming
Sciarrone, Andrea
Sun, Chao
Garibotto, Chiara
Tran, Duong Nguyen-Ngoc
Lavagetto, Fabio
Haleem, Halar
Motorcu, Hakkı
Ateş, Hasan Fehmi
Nguyen, Huy Hung
Jeon, Hyung Joon
Bisio, Igor
Jeon, Jae Wook
Li, Jiahao
Pham, Long Hoang
Jeon, Moongu
Feng, Qianyu
Li, Shengwen
Tran, Tai Huu-Phuong
Pan, Xiao
Song, Young-min
Yao, Yuehan
Du, Yunhao
Xu, Zhenyu
Luo, Zhipeng
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Chen, G., Wang, W., He, Z., Wang, L., Yuan, Y., Zhang, D. ... Luo, Z. (2021). VisDrone-MOT2021: The vision meets drone multiple object tracking challenge results. IEEE/CVF International Conference on Computer Vision (ICCVW) içinde (2839-2846. ss.). Virtual, 27-30 September 2021. https://dx.doi.org/10.1109/ICCVW54120.2021.00318Özet
Vision Meets Drone: Multiple Object Tracking (VisDrone-MOT2021) challenge - the forth annual activity organized by the VisDrone team - focuses on benchmarking UAV MOT algorithms in realistic challenging environments. It is held in conjunction with ICCV 2021. VisDrone-MOT2021 contains 96 video sequences in total, including 56 sequences (~24K frames) for training, 7 sequences (~3K frames) for validation and 33 sequences (~13K frames) for testing. Bounding-box annotations for novel object categories are provided every frame and temporally consistent instance IDs are also given. Additionally, occlusion ratio and truncation ratio are provided as extra useful annotations. The results of eight state-of-the-art MOT algorithms are reported and discussed. We hope that our VisDrone-MOT2021 challenge will facilitate future research and applications in the field of UAV vision. The website of our challenge can be found at http://www.aiskyeye.com/.