Learning a two-stage CNN model for multi-sized building detection in remote sensing images

Though tremendous strides have been made in building recognition, to handle multi-sized buildings is fundamental for all building detection pipelines. We explore the reason of the problem in detecting the multi-sized buildings and find that most convolutional neural network (CNN) based recognition approaches aim to be scale-invariant. The cues for recognizing a 3 pixels tall building are fundamentally different than those for recogjnizing a 300 pixels tall building. To tackle this problem, we design a novel two-stage building detection model which contains the region proposal stage and the classification stage. In the region proposal stage, we propose a novel Multi-size Fusion Region Proposal Network (MFRPN) for extracting the feature of various size building and generating wide size range of region proposals. In the classification stage, a deep CNN model is used to distinguish whether the generated region proposals are building regions or not. In order to achieve better performance, we present an...