Sign inGet started
Paper · arXiv

From Street View Imagery to Street Quality Indicators: Vision Language Inference for the Suburban 15-minute City

Streetscape quality has become a central concern in contemporary urban planning, particularly within the framework of the pedestrian-friendly 15-minute city, where walkability and public-space quality are increasingly recognized as key determinants of urban performance. However, assessing streetscape qualities across large suburban and peri-urban territories remains challenging due to the time and resource demands of conventional field surveys. This paper presents a planning-oriented assessment of streetscape qualities in the north-eastern periphery of Nice (France) using the latest release of SAGAI (Streetscape Analysis with Generative AI), an open-source workflow that leverages vision-l...

AuthorsJoan Perez, Giovanni Fusco
Primary categorycs.CV
Published20 August 2026
Last updated at source20 August 2026
cs.CVcs.LG
Embed this entry
<iframe src="https://silytics.si/embed/item/8ea6d2d2-be30-45f4-97e6-ac9f3e7ed88a" width="420" height="190" style="border:0" loading="lazy" title="Silytics entry"></iframe>

Free, no tracking. More about feeds and embeds.

Silytics shows public metadata from arXiv and links to the original. Information may be incomplete or out of date. Last refreshed 17 October 2026. Licenses and terms of the original apply to the work itself. Not financial, legal or professional advice.