A synthetic texture-invariant dataset for object detection of UAVs

A synthetic dataset for object detection of UAVs

This repository contains a synthetic datasets accompanying the paper Sim2Air - Synthetic aerial dataset for UAV monitoring by Antonella Barisic, Frano Petric and Stjepan Bogdan.

In this paper, we propose to use a texture-invariant representation of objects for aerial object detection. Our approach improves the generalisation and robustness of the object detector. A dataset is created with randomly assigned atypical textures and sufficient diversity and photorealism in all other components such as shape, pose, lighting, scale, background, etc. The results also show improved accuracy in case of distant objects and difficult lighting conditions.

All datasets from the paper are available for download. If you use these datasets for your research, please cite:

@misc{barisic2021sim2air,
      title={Sim2Air - Synthetic aerial dataset for UAV monitoring}, 
      author={Antonella Barisic and Frano Petric and Stjepan Bogdan},
      year={2021},
      eprint={2110.05145},
      archivePrefix={arXiv},
      primaryClass={cs.CV}
}

Datasets

If you want to test your detection results against real data, check out our UAV-Eagle dataset at larics/UAV-Eagle.

Contact

For more information, please contact Antonella Barisic.