Synthesis and Completion of Facades from Satellite Imagery

Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 12347)


Automatic satellite-based reconstruction enables large and widespread creation of urban areas. However, satellite imagery is often noisy and incomplete, and is not suitable for reconstructing detailed building facades. We present a machine learning-based inverse procedural modeling method to automatically create synthetic facades from satellite imagery. Our key observation is that building facades exhibit regular, grid-like structures. Hence, we can overcome the low-resolution, noisy, and partial building data obtained from satellite imagery by synthesizing the underlying facade layout. Our method infers regular facade details from satellite-based image-fragments of a building, and applies them to occluded or under-sampled parts of the building, resulting in plausible, crisp facades. Using urban areas from six cities, we compare our approach to several state-of-the-art image completion/in-filling methods and our approach consistently creates better facade images.


Image synthesis and completion Inverse procedural modeling Satellite imagery 



This research was supported in part by the Intelligence Advanced Research Projects Activity (IARPA) via Department of Interior/ Interior Business Center (DOI/IBC) contract number D17PC00280. Additional support came from National Science Foundation grants #10001387 and #1835739.

Supplementary material

504434_1_En_34_MOESM1_ESM.pdf (951 kb)
Supplementary material 1 (pdf 950 KB)


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© Springer Nature Switzerland AG 2020

Authors and Affiliations

  1. 1.Purdue UniversityWest LafayetteUSA

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