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Wen et al., 2018 - Google Patents

Visdrone-sot2018: The vision meets drone single-object tracking challenge results

Wen et al., 2018

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Document ID
16780492309650671340
Author
Wen L
Zhu P
Du D
Bian X
Ling H
Hu Q
Liu C
Cheng H
Liu X
Ma W
Nie Q
Wu H
Wang L
Perera A
Zhang B
Heo B
Liu C
Li D
Michail E
Chen H
Liu H
Li H
Kompatsiaris I
Cheng J
Fan J
Zhang J
Young Choi J
Li J
Yang J
Choi J
Zhao J
Han J
Zhang K
Duan K
Song K
Avgerinakis K
Lee K
Ding L
Lauer M
Giannakeris P
Zhang P
Wang Q
Xu Q
Huang Q
Liu Q
Laganire R
Zhang R
Yun S
Zhu S
Wu S
Vrochidis S
Tian W
Zhang W
Chen W
Hu W
Wang W
Zhang W
Ding W
He X
Li X
Zhang X
Luo X
Hu X
Meng Y
Kuai Y
Zhao Y
Li Y
Yang Y
Zhang Y
Wang Y
Qi Y
Deng Z
He Z
Publication year
Publication venue
Proceedings of the European conference on computer vision (ECCV) workshops

External Links

Snippet

Single-object tracking, also known as visual tracking, on the drone platform attracts much attention recently with various applications in computer vision, such as filming and surveillance. However, the lack of commonly accepted annotated datasets and standard …
Continue reading at openaccess.thecvf.com (PDF) (other versions)

Classifications

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