UrbanCLIP: Learning Text-enhanced Urban Region Profiling with Contrastive Language-Image Pretraining from the Web

arXiv:2310.18340v2 Announce Type: replace
Abstract: Urban region profiling from web-sourced data is of utmost importance for urban planning and sustainable development. We are witnessing a rising trend of LLMs for various fields, especially dealing with multi-modal data research such as vision-language learning, where the text modality serves as a supplement information for the image. Since textual modality has never been introduced into modality combinations in urban region profiling, we aim to answer two fundamental questions in this paper: i) Can …

abstract arxiv cs.ai cs.cl data data research development fields image importance language llms modal multi-modal planning pretraining profiling research sustainable sustainable development text trend type urban urban planning vision web