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Large-Scale Synthetic Urban Dataset for Aerial Scene Understanding
The geometric extraction and semantic understanding in bird's eye view plays an important role in cyber-physical-social systems (CPSS), because it can help human or intelligent agents (IAs) to perceive larger range of environment. Moreover, due to lack of comprehensive dataset from oblique perspective, fogend deep learning algorithms for this purpose is still in blank. In this paper, we propose a novel method to generate synthetic large-scale dataset for geometric and semantic urban scenedoi:10.1109/access.2020.2976686 fatcat:fwqoi6qjore3jku6jwmdrcayp4