Street view & computer vision

Evaluating urban street views through collective emotional perception from multimodal social media cityscape posts: An R-ECoT-based interpretable framework

Generative AI for urban planning: Designing streetscapes from street-view imagery using diffusion models

Assessing the association between street view–derived perceived liveliness and street thefts

Large-scale measurement of street interface transparency based on street view data and deep learning: A study of first-tier cities in China (Beijing, Shanghai, and Guangzhou)

Proposes a method to measure how transparent street-level building frontages are, at scale, using open street view images and deep learning in three Chinese megacities.

Street View Imagery Analysis in a Computational Notebook

A hands-on methods chapter showing how to download street view images and apply deep convolutional networks to detect and measure features of the built environment, in a reproducible notebook.

Learning street view representations based on a spatiotemporal contrastive learning framework

Benchmarks representation-learning strategies for street view imagery and introduces a spatiotemporal contrastive framework to learn features useful for perception and socioeconomic prediction tasks.