UA-DETRAC: A new benchmark and protocol for multi-object detection and tracking-Reference-Cited by-同舟云学术

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UA-DETRAC: A new benchmark and protocol for multi-object detection and tracking

Published:2020-04 Issue: Volume:193 Page:102907
ISSN:1077-3142
Container-title:Computer Vision and Image Understanding
language:en
Short-container-title:Computer Vision and Image Understanding

Author:

Wen Longyin,Du Dawei,Cai Zhaowei,Lei Zhen,Chang Ming-Ching,Qi Honggang,Lim Jongwoo,Yang Ming-Hsuan,Lyu Siwei

Funder

National Natural Science Foundation of China

National Science Foundation

Publisher

Elsevier BV

Subject

Computer Vision and Pattern Recognition,Signal Processing,Software

Reference98 articles.

1. Amin, S., Galasso, F., 2017. Geometric proposals for faster R-CNN. In: AVSS, pp. 1–6.

2. Andriluka, M., Roth, S., Schiele, B., 2008. People-tracking-by-detection and people-detection-by-tracking. In: Proceedings of IEEE Conference on Computer Vision and Pattern Recognition.

3. Andriyenko, A., Schindler, K., 2011. Multi-target tracking by continuous energy minimization. In: Proceedings of IEEE Conference on Computer Vision and Pattern Recognition. pp. 1265–1272.

4. Andriyenko, A., Schindler, K., Roth, S., 2012. Discrete-continuous optimization for multi-target tracking, In: Proceedings of IEEE Conference on Computer Vision and Pattern Recognition, pp. 1926–1933.

5. Bae, S.H., Yoon, K., 2014. Robust online multi-object tracking based on tracklet confidence and online discriminative appearance learning. In: Proceedings of IEEE Conference on Computer Vision and Pattern Recognition, pp. 1218–1225.

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