  Housing quality is an essential proxy for regional wealth, security and
health. Understanding the distribution of housing quality is crucial for
unveiling rural development status and providing political proposals.
However,present rural house quality data highly depends on a top-down,
time-consuming survey at the national or provincial level but fails to unpack
the housing quality at the village level. To fill the gap between accurately
depicting rural housing quality conditions and deficient data,we collect
massive rural images and invite users to assess their housing quality at scale.
Furthermore, a deep learning framework is proposed to automatically and
efficiently predict housing quality based on crowd-sourcing rural images.
