To automatically generate data for training deep convolutional neural network models to segment building facades, researchers used a three-dimensional model and game engine to generate digital city twin synthetic training data. They found that a model trained on these data mixed with some real data was competitive with a model trained on real data alone, revealing the potential of digital twin data to improve accuracy and replace costly manually annotated real data.