The AeroScapes aerial semantic segmentation benchmark comprises of images captured using a commercial drone from an altitude range of 5 to 50 metres. The dataset provides 3269 720p images and ground-truth masks for 11 classes.
Clone the repository
git clone email@example.com:ishann/aeroscapes.git
Download the data
This results in the following directory
data/ aeroscapes/ JPEGImages/ 3269 RGB images. SegmentationClass/ 3269 ground-truth segmentation masks. Visualizations/ 3269 RGB ground-truth segmentation visualizations. ImageSets/ Training and validation splits for data. aeroscapes.tar.gz Downloaded file (local reference to avoid need for repeated downloads).
If you use AeroScapes in your research, please cite the following:
Ensemble Knowledge Transfer for Semantic Segmentation Ishan Nigam, Chen Huang, Deva Ramanan Proceedings of the 2018 IEEE Winter Conference on Applications of Computer Vision
We acknowledge the efforts of Autel Robotics in the collection and manual annotation of the dataset.
Questions and Comments
For comments and feedback, contact Ishan Nigam at firstname.lastname@example.org.