Get an overview of the SkyScapes dataset, its main features, the label policy, and the definitions of contained semantic classes.
The SkyScapes dataset
SkyScapes respresents a new large-scale dataset that contains a diverse set of aerial images in aerial scenes from multiple different locations with fine-grained high-quality pixel-level annotations comprised of 70000 instance objects including lane-markings. The dataset is thus by far the most diverse dataset than similar previous attempts. Details on annotated classes and examples of our annotations are available at this webpage.
TheSkyScapes Dataset is intended for
assessing the performance of vision algorithms for major tasks of semantic aerial scene understanding: pixel-level labeling
supporting research that aims to exploit small and large objects for training deep neural networks.
October 1st 2023: Airborne-Shadow (ASD) dataset becomes online
SkyScapes is now available for download and benchmarking. […]
This SkyScapes Dataset is made freely available to academic and non-academic entities for non-commercial purposes such as academic research, teaching, scientific publications, or personal experimentation. Permission is granted to use the data given that you agree to our license terms.
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