With the rise of GeoAI research, streetscape imagery has received extensive attention due to its comprehensive coverage, abundant information, and accessibility. However, obtaining a holistic spatial–temporal scene representation is difficult because places are often composed of multiple images from different angles, times and locations. This problem also exists in other types of geo-tagged imagery. To solve it, we propose a purely visual, robust, and reliable method for urban function iden...
