The Unmanned Aerial Vehicle Benchmark: Object Detection and Tracking-Reference-Cited by-同舟云学术

The Unmanned Aerial Vehicle Benchmark: Object Detection and Tracking

Published:2018 Issue: Volume: Page:375-391
ISSN:0302-9743
Container-title:Computer Vision – ECCV 2018
language:
Short-container-title:

Author:

Du Dawei^ORCID,Qi Yuankai^ORCID,Yu Hongyang^ORCID,Yang Yifan^ORCID,Duan Kaiwen^ORCID,Li Guorong^ORCID,Zhang Weigang^ORCID,Huang Qingming^ORCID,Tian Qi^ORCID

Publisher

Springer International Publishing

Link

http://link.springer.com/content/pdf/10.1007/978-3-030-01249-6_23

Reference54 articles.

1. Mot17 challenge. https://motchallenge.net/

2. Bae, S.H., Yoon, K.: Robust online multi-object tracking based on tracklet confidence and online discriminative appearance learning. In: CVPR, pp. 1218–1225 (2014)

3. Barekatain, M., et al.: Okutama-action: an aerial view video dataset for concurrent human action detection. In: CVPRW, pp. 2153–2160 (2017)

4. Bernardin, K., Stiefelhagen, R.: Evaluating multiple object tracking performance: The CLEAR MOT metrics. EURASIP J. Image Video Process. 2008(2008)

5. Lecture Notes in Computer Science;L Bertinetto,2016

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