Conditional GIS-Aware Network for Individual Building Segmentation in a VHR SAR Image

In this paper, we propose a network for individual building segmentation from a single VHR SAR image. The proposed network employs building footprints from GIS data in learning multi-level visual features to predict building masks in the SAR image. Experimental results over Berlin show that the proposed network effectively brings improvements with variant backbones. In addition, we propose an approach for generating building labels from an accurate digital elevation model (DEM), which can be used to generate large-scale SAR image datasets.