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VisDrone-DET2019: The Vision Meets Drone Object Detection in Image Challenge Results

: Du, Dawei; Schumann, Arne; Sommer, Lars; Steinmann, Lucas; Meier, Jonas et al.

Postprint urn:nbn:de:0011-n-5968591 (1.2 MByte PDF)
MD5 Fingerprint: a505005ef81ea052e0622241890e5e07
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Created on: 23.7.2020

Institute of Electrical and Electronics Engineers -IEEE-; IEEE Computer Society:
IEEE/CVF International Conference on Computer Vision Workshops, ICCVW 2019. Proceedings : 27 October - 2 November 2019, Seoul, Korea
Los Alamitos, Calif.: IEEE Computer Society Conference Publishing Services (CPS), 2019
ISBN: 978-1-7281-5024-6
ISBN: 978-1-7281-5023-9
International Conference on Computer Vision (ICCV) <17, 2019, Seoul>
OpenEDS Workshop <2019, Seoul>
Conference Paper, Electronic Publication
Fraunhofer IOSB ()

Recently, automatic visual data understanding from drone platforms becomes highly demanding. To facilitate the study, the Vision Meets Drone Object Detection in Image Challenge is held the second time in conjunction with the 17-th International Conference on Computer Vision (ICCV 2019), focuses on image object detection on drones. Results of 33 object detection algorithms are presented. For each participating detector, a short description is provided in the appendix. Our goal is to advance the state-of-the-art detection algorithms and provide a comprehensive evaluation platform for them. The evaluation protocol of the VisDrone-DET2019 Challenge and the comparison results of all the submitted detectors on the released dataset are publicly available at the website: http: // The results demonstrate that there still remains a large room for improvement for object detection algorithms on drones.