ISPRS Benchmark on Object Detection in High-Resolution Satellite Images

This benchmark is supported by 2021 ISPRS scientific initiatives project.

Project Goals

This ISPRS benchmark provides an effective way for the evaluation and comparison of object detection and recognition in high-resolution satellite images. Datasets are available from this webpage and the mirror website （http://gaofen-challenge.com/）. Interested participants can test their methods and submit their results for evaluation. The list of submitted evaluation results will be updated on the mirror website.

Activities and Benchmark Datasets

This benchmark provides a large-scale dataset and an evaluation submitting system for applying advanced deep learning technology to remote sensing. Images in the benchmark are mainly collected from the Gaofen satellites. There are more than 1 million instances and more than 15,000 images in this benchmark. As shown in Figure 1, all objects in the dataset are annotated with respect to 5 categories and 37 sub-categories by oriented bounding boxes. Each image is of the size in the range from 1000 × 1000 to 10,000 × 10,000 pixels and contains objects exhibiting a wide variety of scales, orientations, and shapes.

We provide raw data of training set with ground truth for users’ evaluation. We also provide raw data of test set for evaluation by submitting. The evaluation metrics and the format for submitting results can be seen on the mirror website （http://gaofen-challenge.com/）.

Condition of Use

The download of the datasets is subjected to the following conditions:

• Datasets must be used for research purposes only. Any other use is prohibited.
• Datasets must not be distributed to third parties. Any person interested in the data may obtain them via ISPRS WG I/6.
• If the datasets are used in any publication, please acknowledge the ISPRS WG I/6 for the provision of the data, and cite the Benchmark paper. This paper will be published later. Please wait and keep following.

FAIR1M: A Benchmark Dataset for Fine-grained Object Recognition in High-Resolution Remote Sensing Imagery[J]. arXiv preprint arXiv:2103.05569, 2021.

Figure 1 Examples of Annotated Images

Download and Evaluation

Please visit http://gaofen-challenge.com/ to download the data and submit the evaluation results.

Investigators

Dr. Xian Sun (Principal Investigator)

Chinese Academy of Sciences, China

Dr. Cheng Wang (Co-Investigator)

Xiamen University, China

Dr. Martin Weinmann (Co-Investigator)

Karlsruhe Institute of Technology, Germany