VisDrone-DET2021: The Vision Meets Drone Object detection Challenge Results

Yaru Cao, Zhijian He, Lujia Wang, Wenguan Wang, Yixuan Yuan, Dingwen Zhang, Jinglin Zhang, Pengfei Zhu, Luc Van Gool, Junwei Han, Steven Hoi, Qinghua Hu, Ming Liu, Chong Cheng, Fanfan Liu, Guojin Cao, Guozhen Li, Hongkai Wang, Jianye He, Junfeng WanQi Wan, Qi Zhao, Shuchang Lyu, Wenzhe Zhao, Xiaoqiang Lu, Xingkui Zhu, Yingjie Liu, Yixuan Lv, Yujing Ma, Yuting Yang, Zhe Wang, Zhenyu Xu, Zhipeng Luo, Zhimin Zhang, Zhiguang Zhang, Zihao Li, Zixiao Zhang

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

205 Scopus citations

Abstract

Object detection on the drone faces a great diversity of challenges such as small object inference, background clutter and wide viewpoint. In contrast to traditional detection problem in computer vision, object detection in bird-like angle can not be transplanted directly from common-in-use methods due to special object texture in sky's view. However, due to the lack of a comprehensive data set, the number of algorithms that focus on object detection using data captured by drones is limited. So the VisDrone team gathered a massive data set and organized Vision Meets Drones: A Challenge (VisDrone2021) in conjunction with the IEEE International Conference on Computer Vision (ICCV 2021) to advance the field. The collected dataset is the same as the previous dataset object detection challenge. Specifically, the team needed to predict the bounding boxes of the objects of ten predefined classes. We received results from a number of teams using different approaches, and this article describes the 8 team's approach. We conducted a detailed analysis of the assessment results and summarized the challenges. More information can be found at: http://www.aiskyeye.com/.

Original languageEnglish
Title of host publicationProceedings - 2021 IEEE/CVF International Conference on Computer Vision Workshops, ICCVW 2021
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages2847-2854
Number of pages8
ISBN (Electronic)9781665401913
DOIs
StatePublished - 2021
Event18th IEEE/CVF International Conference on Computer Vision Workshops, ICCVW 2021 - Virtual, Online, Canada
Duration: 11 Oct 202117 Oct 2021

Publication series

NameProceedings of the IEEE International Conference on Computer Vision
Volume2021-October
ISSN (Print)1550-5499

Conference

Conference18th IEEE/CVF International Conference on Computer Vision Workshops, ICCVW 2021
Country/TerritoryCanada
CityVirtual, Online
Period11/10/2117/10/21

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