  The condition of a building is an important factor for real estate valuation.
Currently, the estimation of condition is determined by real estate appraisers
which makes it subjective to a certain degree. We propose a novel vision-based
approach for the assessment of the building condition from exterior views of
the building. To this end, we develop a multi-scale patch-based pattern
extraction approach and combine it with convolutional neural networks to
estimate building condition from visual clues. Our evaluation shows that
visually estimated building condition can serve as a proxy for condition
estimates by appraisers.
