Real-world aerial scene understanding is limited by a lack of datasets that contain densely annotated images curated under a diverse set of conditions. Due to inherent challenges in obtaining such images in controlled real-world settings, we present SkyScenes, a synthetic dataset of densely annotated aerial images captured from Unmanned Aerial Vehicle (UAV) perspectives.
We carefully curate SkyScenes images from CARLA to comprehensively capture diversity across layout (urban and rural maps), weather conditions, times of day, pitch angles and altitudes with corresponding semantic, instance and depth annotations.
Through our experiments using SkyScenes, we show that :
@misc{khose2023skyscenes,
title={SkyScenes: A Synthetic Dataset for Aerial Scene Understanding},
author={Sahil Khose and Anisha Pal and Aayushi Agarwal and Deepanshi and Judy Hoffman and Prithvijit Chattopadhyay},
year={2023},
eprint={2312.06719},
archivePrefix={arXiv},
primaryClass={cs.CV}
}