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Detecting and Tracking Small and Dense Moving Objects in Satellite Videos: A Benchmark
This is the official website of the VISO (VIdeo Satellite Objects) dataset. [Google Drive][BaiduYun](Sharing code: viso)
(1) Data
This dataset is a large-scale dataset for moving object detection and tracking in satellite videos, which consists of 40 satellite videos captured by Jilin-1 satellite platforms. Each image has a resolution of 12000x5000 and contains a great number of objects with different scales. Four common types of vechicles, including plane, car, ship, and train, are manually-labeled. A total of 853,911 instances are labeled by axis-aligned bounding boxes.
<p align="center"> <img src="figs/Fig1.png" width="100%"> </p> <p align="center"> <img src="figs/Fig2.png" width="100%"> </p>(2) Benchmark
We also build a new satellite video benchmark to fairly and extensively evaluate the performance of existing methods in several sub-tasks, including moving object detection, single-object tracking, and multi-object tracking.
- Moving Object Detection:
- Single Object Tracking:
- Multiple Object Tracking:
(3) Demo
<p align="center"> <a href="https://youtu.be/NctUdpQBbAU"><img src="./figs/Demo_cover_fig1.png" width="50%"></a> </p> <p align="center"> <a href="https://youtu.be/KaabG_zrkEM"><img src="./figs/Demo_cover_fig2.png" width="50%"></a> </p>License
The provided dataset has been authorized by Changguang Satellite Technology Co., Ltd.. Licensed under the CC BY-NC-SA 4.0 license, see LICENSE.
Citation
If you find our work useful in your research, please consider citing:
@article{yin2021detecting,
title={Detecting and Tracking Small and Dense Moving Objects in Satellite Videos: A Benchmark},
author={Yin, Qian and Hu, Qingyong and Liu, Hao and Zhang, Feng and Wang, Yingqian and Lin, Zaiping and An, Wei and Guo, Yulan},
journal={IEEE Transactions on Geoscience and Remote Sensing},
year={2021},
publisher={IEEE}
}
Contact
Please contact qingyong.hu@cs.ox.ac.uk if you have any questions.
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