CNNs Fusion for Building Detection in Aerial Images for the Building Detection Challenge

Abstract

This paper presents our contribution to the DeepGlobe Building Detection Challenge. We enhanced the SpaceNet Challenge winning solution by proposing a new fusion strategy based on a deep combiner using segmentation both results of different CNN and input data to segment. Segmentation results for all cities have been significantly improved (between 1% improvement over the baseline for the smallest one to more than 7% for the biggest one). The separation of adjacent buildings should be the next enhancement made to the solution.