Abstract: Automated three-dimensional (3D) building model estimation is disclosed. In an embodiment, a method comprises: obtaining, using one or more processors, an aerial image of a building based on an input address; obtaining, using the one or more processors, three-dimensional (3D) data containing the building based on the input address; pre-processing the aerial image and 3D data; reconstructing, using the one or more processors, a 3D building model from the pre-processed image and 3D data, the reconstructing including: predicting, using instance segmentation, a mask for each roof face; converting each roof face into a two-dimensional (2D) polygon; and projecting each 2D polygon into a 3D polygon representing the 3D building model.

Abstract: Automated three-dimensional (3D) building model estimation is disclosed that predicts roof top outlines, pitches and heights based on imagery and 3D data. In an embodiment, a method comprises: obtaining an aerial image of a building based on an input address; obtaining three-dimensional (3D) data containing the building based on the input address; pre-processing the aerial image and 3D data; reconstructing a 3D building model from the pre-processed image and 3D data, the reconstructing including: predicting, using instance segmentation, a mask for each roof component of the building; predicting, using a first machine learning model with the mask as input, an outline for each roof component; predicting, using a second machine learning mode with the mask and outline as input, a pitch and height of each roof component; and rendering the 3D building model based on the predicted outline, pitch and height of each roof component.

Abstract: Automated three-dimensional (3D) building model estimation is disclosed. In an embodiment, a method comprises: obtaining, using one or more processors, an aerial image of a building based on an input address; obtaining, using the one or more processors, three-dimensional (3D) data containing the building based on the input address; pre-processing the aerial image and 3D data; reconstructing, using the one or more processors, a 3D building model from the pre-processed image and 3D data, the reconstructing including: predicting, using instance segmentation, a mask for each roof face; converting each roof face into a two-dimensional (2D) polygon; and projecting each 2D polygon into a 3D polygon representing the 3D building model.