"Does the cafe entrance look accessible? Where is the door?" Towards Geospatial AI Agents for Visual Inquiries
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arXiv
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| Main Authors: | , , , , , , , , , |
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| Format: | Preprint |
| Published: |
2025
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| _version_ | 1866912547490234368 |
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| author | Froehlich, Jon E. Hwang, Jared Wang, Zeyu O'Meara, John S. Su, Xia Huang, William Zhang, Yang Fiannaca, Alex Nelson, Philip Kane, Shaun |
| author_facet | Froehlich, Jon E. Hwang, Jared Wang, Zeyu O'Meara, John S. Su, Xia Huang, William Zhang, Yang Fiannaca, Alex Nelson, Philip Kane, Shaun |
| contents | Interactive digital maps have revolutionized how people travel and learn about the world; however, they rely on pre-existing structured data in GIS databases (e.g., road networks, POI indices), limiting their ability to address geo-visual questions related to what the world looks like. We introduce our vision for Geo-Visual Agents--multimodal AI agents capable of understanding and responding to nuanced visual-spatial inquiries about the world by analyzing large-scale repositories of geospatial images, including streetscapes (e.g., Google Street View), place-based photos (e.g., TripAdvisor, Yelp), and aerial imagery (e.g., satellite photos) combined with traditional GIS data sources. We define our vision, describe sensing and interaction approaches, provide three exemplars, and enumerate key challenges and opportunities for future work. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2508_15752 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | "Does the cafe entrance look accessible? Where is the door?" Towards Geospatial AI Agents for Visual Inquiries Froehlich, Jon E. Hwang, Jared Wang, Zeyu O'Meara, John S. Su, Xia Huang, William Zhang, Yang Fiannaca, Alex Nelson, Philip Kane, Shaun Human-Computer Interaction Artificial Intelligence Computer Vision and Pattern Recognition H.5; I.2 Interactive digital maps have revolutionized how people travel and learn about the world; however, they rely on pre-existing structured data in GIS databases (e.g., road networks, POI indices), limiting their ability to address geo-visual questions related to what the world looks like. We introduce our vision for Geo-Visual Agents--multimodal AI agents capable of understanding and responding to nuanced visual-spatial inquiries about the world by analyzing large-scale repositories of geospatial images, including streetscapes (e.g., Google Street View), place-based photos (e.g., TripAdvisor, Yelp), and aerial imagery (e.g., satellite photos) combined with traditional GIS data sources. We define our vision, describe sensing and interaction approaches, provide three exemplars, and enumerate key challenges and opportunities for future work. |
| title | "Does the cafe entrance look accessible? Where is the door?" Towards Geospatial AI Agents for Visual Inquiries |
| topic | Human-Computer Interaction Artificial Intelligence Computer Vision and Pattern Recognition H.5; I.2 |
| url | https://arxiv.org/abs/2508.15752 |