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dc.contributor.author
Liu, Zhihao
dc.contributor.author
He, Zhijian
dc.contributor.author
Wang, Lujia
dc.contributor.author
Wang, Wenguan
dc.contributor.author
Yuan, Yixuan
dc.contributor.author
Zhang, Dingwen
dc.contributor.author
Zhang, Jinglin
dc.contributor.author
Zhu, Pengfei
dc.contributor.author
Van Gool, Luc
dc.contributor.author
Han, Junwei
dc.contributor.author
Hoi, Steven
dc.contributor.author
Hu, Qinghua
dc.contributor.author
Liu, Ming
dc.contributor.author
Pan, Junwen
dc.contributor.author
Yin, Baoqun
dc.contributor.author
Zhang, Binyu
dc.contributor.author
Liu, Chengxin
dc.contributor.author
Ding, Ding
dc.contributor.author
Liang, Dingkang
dc.contributor.author
Ding, Guanchen
dc.contributor.author
et al.
dc.date.accessioned
2022-03-15T15:11:19Z
dc.date.available
2022-02-25T04:21:16Z
dc.date.available
2022-03-15T15:11:19Z
dc.date.issued
2021
dc.identifier.isbn
978-1-6654-0191-3
en_US
dc.identifier.isbn
978-1-6654-0192-0
en_US
dc.identifier.other
10.1109/ICCVW54120.2021.00317
en_US
dc.identifier.uri
http://hdl.handle.net/20.500.11850/534132
dc.description.abstract
Crowding counting research evolves quickly by the leverage of development in deep learning. Many researchers put their efforts into crowd counting tasks and have achieved many significant improvements. However, current datasets still barely satisfy this evolution and high quality evaluation data is urgent. Motivated by high quality and quantity study in crowding counting, we collect a drone-captured dataset formed by 5,468 images(images in RGB and thermal appear in pairs and 2,734 respectively). There are 1,807 pairs of images for training, and 927 pairs for testing. We manually annotate persons with points in each frame. Based on this dataset, we organized the Vision Meets Drone Crowd Counting Challenge(Visdrone-CC2021) in conjunction with the International Conference on Computer Vision (ICCV 2021). Our challenge attracts many researchers to join, which pave the road of speed up the milestone in crowding counting. To summarize the competition, we select the most remarkable algorithms from participants' submissions and provide a detailed analysis of the evaluation results. More information can be found at the website: http : //www. aiskyeye.com/.
en_US
dc.language.iso
en
en_US
dc.publisher
IEEE
en_US
dc.title
VisDrone-CC2021: The Vision Meets Drone Crowd Counting Challenge Results
en_US
dc.type
Conference Paper
dc.date.published
2021-11-24
ethz.book.title
2021 IEEE/CVF International Conference on Computer Vision Workshops (ICCVW)
en_US
ethz.pages.start
2830
en_US
ethz.pages.end
2838
en_US
ethz.event
2021 IEEE/CVF International Conference on Computer Vision (ICCVW 2021)
en_US
ethz.event.location
Online
en_US
ethz.event.date
October 11-17, 2021
en_US
ethz.identifier.wos
ethz.publication.place
Piscataway, NJ
en_US
ethz.publication.status
published
en_US
ethz.date.deposited
2022-02-25T04:21:26Z
ethz.source
WOS
ethz.eth
yes
en_US
ethz.availability
Metadata only
en_US
ethz.rosetta.installDate
2022-03-15T15:11:27Z
ethz.rosetta.lastUpdated
2022-03-15T15:11:27Z
ethz.rosetta.versionExported
true
ethz.COinS
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