Mix MSTAR is a new synthetic SAR vehicle dataset,consisting of 100 large images with 5392 vehicles of 20 fine-grained categories. The geographically contiguous test set can be stitched into four large-scale images. The arrangement of vehicles is diverse, with both tight and sparse groupings and various scenes such as urban, highway, grassland, and forest.
Currently, the dataset can be obtained through losonjay@163.com.(2023/12/3)
If you use this dataset or article in your research, please cite this project.
@article{liu2023mix,
title={Mix MSTAR: A Synthetic Benchmark Dataset for Multi-Class Rotation Vehicle Detection in Large-Scale SAR Images},
author={Liu, Zhigang and Luo, Shengjie and Wang, Yiting},
journal={Remote Sensing},
volume={15},
number={18},
pages={4558},
year={2023},
publisher={MDPI}
}If you use this toolbox or benchmark in your research, please cite this project.
@inproceedings{zhou2022mmrotate,
title = {MMRotate: A Rotated Object Detection Benchmark using PyTorch},
author = {Zhou, Yue and Yang, Xue and Zhang, Gefan and Wang, Jiabao and Liu, Yanyi and
Hou, Liping and Jiang, Xue and Liu, Xingzhao and Yan, Junchi and Lyu, Chengqi and
Zhang, Wenwei and Chen, Kai},
booktitle={Proceedings of the 30th ACM International Conference on Multimedia},
year={2022}
}