CitySurfaces
![](https://urbantk.org/wp-content/uploads/2023/12/overview-2-1024x268.jpg)
CitySurfaces is a framework that combines active learning and semantic segmentation to locate, delineate, and classify sidewalk paving materials from street-level images. Our framework adopts a recent high-performing semantic segmentation model (Tao et al., 2020), which uses hierarchical multi-scale attention combined with object-contextual representations.
The framework was presented in our paper published at the Sustainable Cities and Society journal (Arxiv link here).
For more information, check our GitHub project: https://github.com/VIDA-NYU/city-surfaces