Most urban applications necessitate building footprints in the form of concise vector graphics with sharp boundaries rather than pixel-wise raster images. This need contrasts with the majority of existing methods, which typically generate …
Deep learning methods are typically data-hungry and require many labelled samples. Unfortunately, the amount of effort required to label the data has significantly hindered the application of deep learning methods, especially in 3D modelling tasks …
Realistic and delicate window models are in great demand for detailed LOD-3 urban reconstruction. However, current research tends to oversimplify the window models due to the difficulties in describing the complex window types and structure …