/CG-Net

Learning Calibrated-Guidance for Object Detection in Aerial Images

Primary LanguagePythonApache License 2.0Apache-2.0

Learning Calibrated-Guidance for Object Detection in Aerial Images

Paper can be seen here https://arxiv.org/abs/2103.11399

Introduction

This codebase is created to build benchmarks for object detection in aerial images. It is modified from mmdetection. The master branch works with PyTorch 1.1 or higher. If you would like to use PyTorch 0.4.1, please checkout to the pytorch-0.4.1 branch.

License

This project is released under the Apache 2.0 license.

  • You can find the detailed configs in configs/DOTA.
  • The trained models are available at Google Drive.

Installation

Please refer to INSTALL.md for installation.

Get Started

Please see GETTING_STARTED.md for the basic usage of mmdetection.

Contributing

We appreciate all contributions to improve benchmarks for object detection in aerial images.

Citing

If you use our work, please consider cite:

@InProceedings{liang2021learning,
      title={Learning Calibrated-Guidance for Object Detection in Aerial Images}, 
      author={Dong, Liang and Zongqi, Wei and Dong, Zhang and Qixiang, Geng and Liyan, Zhang and Han, Sun and Huiyu, Zhou and Mingqiang, Wei and Pan, Gao},
      booktitle ={arXiv:2103.11399},
      year={2021}
}

Thanks to the Third Party Libs

Pytorch

mmdetection

AerialDetection