Introduced in Very Deep Convolutional Networks for Large-Scale Image Recognition2016
The INRIA Aerial Image Labeling dataset is comprised of 360 RGB tiles of 5000×5000px with a spatial resolution of 30cm/px on 10 cities across the globe. Half of the cities are used for training and are associated to a public ground truth of building footprints. The rest of the dataset is used only for evaluation with a hidden ground truth. The dataset was constructed by combining public domain imagery and public domain official building footprints.
Source: Distance transform regression for spatially-aware deep semantic segmentation Image Source: https://project.inria.fr/aerialimagelabeling/
Unknown
