GeoFormer achieves 3.19 m building-height RMSE with 0.32 M parameters by applying windowed local attention to Sentinel imagery, outperforming CNN baselines by 7.5 % while releasing all code and weights.
SHAFTS (v2022.3): A deep- learning-based Python package for simultaneous extraction of building height and footprint from Sentinel imagery
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GeoFormer: A Lightweight Swin Transformer for Joint Building Height and Footprint Estimation from Sentinel Imagery
GeoFormer achieves 3.19 m building-height RMSE with 0.32 M parameters by applying windowed local attention to Sentinel imagery, outperforming CNN baselines by 7.5 % while releasing all code and weights.