As the interest in autonomous systems continues to grow, one of the major
challenges is collecting sufficient and representative real-world data. Despite
the strong practical and commercial interest in autonomous landing systems in
the aerospace field, there is a lack of open-source datasets of aerial images.
To address this issue, we present a dataset-lard-of high-quality aerial images
for the task of runway detection during approach and landing phases. Most of
the dataset is composed of synthetic images but we also provide manually
labelled images from real landing footages, to extend the detection task to a
more realistic setting. In addition, we offer the generator which can produce
such synthetic front-view images and enables automatic annotation of the runway
corners through geometric transformations. This dataset paves the way for
further research such as the analysis of dataset quality or the development of
models to cope with the detection tasks. Find data, code and more up-to-date
information at this https URL

介绍了一个高质量的航空景象数据集，其中包括大量的合成图像和手动标注的真实着陆图像，以应对自主降落系统中数据不足和缺乏开源数据集的问题并支持跑道检测等任务。