OpenCity3D: What do Vision-Language Models know about Urban
  Environments?
Vision-language models (VLMs) show great promise for 3D scene understanding
but are mainly applied to indoor spaces or autonomous driving, focusing on
low-level tasks like segmentation. This work expands their use to urban-scale
environments by leveraging 3D reconstructions from multi-view aerial imagery.
We propose OpenCity3D, an approach that addresses high-level tasks, such as
population density estimation, building age classification, property price
prediction, crime rate assessment, and noise pollution evaluation. Our findings
highlight OpenCity3D's impressive zero-shot and few-shot capabilities,
showcasing adaptability to new contexts. This research establishes a new
paradigm for language-driven urban analytics, enabling applications in
planning, policy, and environmental monitoring. See our project page:
opencity3d.github.io
67e3d39948da72bf6f3d27f7
Valentin Bieri
claimed_verified
2025-04-10T15:45:37.266Z
67d42d13d70098db698e8453
/avatars/0956711c9028edf871e41d10a3464bc9.svg
Valentin Bieri
user
bieriv
67e3d39948da72bf6f3d27f8
Marco Zamboni
67e3d39948da72bf6f3d27f9
Nicolas S. Blumer
67e3d39948da72bf6f3d27fa
Qingxuan Chen
claimed_verified
2025-03-26T20:44:10.272Z
64462645866784561a882802
/avatars/4c08f6f60a82b7292c91fccb2c8bea37.svg
Qingxuan Chen
user
LUC1O
67e3d39948da72bf6f3d27fb
Francis Engelmann
claimed_verified
2025-05-18T08:47:51.883Z
671a7160e45d92e304e82f45
https://cdn-avatars.huggingface.co/v1/production/uploads/no-auth/-trHIg97qX0dE9T4UYycc.png
Francis Engelmann
user
francisengelmann
OpenCity3D: What do Vision-Language Models know about Urban
  Environments?
Vision-language models (VLMs) show great promise for 3D scene understanding
but are mainly applied to indoor spaces or autonomous driving, focusing on
low-level tasks like segmentation. This work expands their use to urban-scale
environments by leveraging 3D reconstructions from multi-view aerial imagery.
We propose OpenCity3D, an approach that addresses high-level tasks, such as
population density estimation, building age classification, property price
prediction, crime rate assessment, and noise pollution evaluation. Our findings
highlight OpenCity3D's impressive zero-shot and few-shot capabilities,
showcasing adaptability to new contexts. This research establishes a new
paradigm for language-driven urban analytics, enabling applications in
planning, policy, and environmental monitoring. See our project page:
opencity3d.github.io
OpenCity3D leverages vision-language models for high-level urban analytics tasks using 3D reconstructions from aerial imagery, demonstrating zero-shot and few-shot capabilities.
vision-language models VLMs 3D scene understanding 3D reconstructions aerial imagery population density estimation building age classification property price prediction crime rate assessment noise pollution evaluation zero-shot capabilities few-shot capabilities language-driven urban analytics