GeoRGMAE: Geospatially Guided Masked Autoencoders for Building Segmentation
The proposed GeoRGMAE, a geospatially guided masked autoencoder pretraining strategy for building segmentation, introduces three masking strategies that prioritize semantically relevant building regions under the varying urban densities and suggests that incorporating geospatial priors into masked image modelling (MIM)...