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• W2910365069 abstract "As we begin to consider modeling large, realistic 3D building scenes, it becomes necessary to consider a more compact representation over the polygonal mesh model. Due to the large amounts of annotated training data, which is costly to obtain, we leverage synthetic data to train our system for the satellite image domain. By utilizing the synthetic data, we formulate the building decomposition as an application of instance segmentation and primitive fitting to decompose a building into a set of primitive shapes. Experimental results on WorldView-3 satellite image dataset demonstrate the effectiveness of our 3D building modeling approach." @default.
• W2910365069 created "2019-01-25" @default.
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• W2910365069 date "2019-01-16" @default.
• W2910365069 modified "2023-09-23" @default.
• W2910365069 title "Primitive-based 3D Building Modeling, Sensor Simulation, and Estimation" @default.
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• W2910365069 doi "https://doi.org/10.48550/arxiv.1901.05554" @default.
• W2910365069 hasPublicationYear "2019" @default.
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