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Abstract. Building footprint extraction (BFE) from multi-sensor data such as optical images and light detection and ranging (LiDAR) point clouds is widely used in various fields of remote sensing applications. However, it is still challenging research topic due to relatively inefficient building extraction techniques from variety of complex scenes in multi-sensor data. In this study, we develop and evaluate a deep competition network (DCN) that fuses very high spatial resolution optical remotedoi:10.5194/isprs-archives-xlii-4-w18-615-2019 fatcat:22vcl6pfg5euvc2kuic2zvlh6y