ArtScape

Urban art brings cultural expression, community identity, and aesthetic enrichment to cities. Currently, there are no systematic ways of exploring urban art at scale. We introduce ArtScape, a VLM-based interactive tool that lets users view, search, filter, and tour four categories of art (murals, mosaics, sculptures, graffiti). To comprehensively and automatically detect urban artwork throughout a region, we designed a custom five-stage pipeline that uses VLMs to detect and describe urban artwork within 360° panoramic Street View images, achieving a micro-F1 of 0.83 on an urban art dataset we labeled. ArtScape categorizes, describes, and scores the reachability and interestingness of each artwork while deduplicating based on proximity and similarity. We evaluated this tool with 12 participants spanning urban planners, artists, sighted users, and blind and low vision users. Our findings show that ArtScape’s at-scale AI artwork curation enables granular and aggregate urban art discovery, thereby helping people learn about their communities and city-wide trends, motivating in-person urban exploration, and expanding perceptions of what constitutes urban art.