# Primitive-based 3D Building Modeling, Sensor Simulation, and Estimation

arXiv: https://arxiv.org/abs/1901.05554 · HTML: https://mlsanity.com/paper/1901.05554/

## Key facts

- Cited by 3 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 16 Jan 2019.

## Built on by (most cited first, 3 of 3)

- [Automated LoD-2 Model Reconstruction from Very-HighResolution Satellite-derived Digital Surface Model and Orthophoto](https://mlsanity.com/paper/2109.03876/) (2021)
- [Cumulative Assessment for Urban 3D Modeling](https://mlsanity.com/paper/2107.04622/) (2021)
- [Physics Driven Image Simulation from Commercial Satellite Imagery](https://mlsanity.com/paper/2504.15378/) (2025)

## Abstract (arXiv)

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.