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UrbanVLP: A Multi-Granularity Vision-Language Pre-Trained Foundation Model for Urban Indicator Prediction
March 26, 2024, 4:48 a.m. | Xixuan Hao, Wei Chen, Yibo Yan, Siru Zhong, Kun Wang, Qingsong Wen, Yuxuan Liang
cs.CV updates on arXiv.org arxiv.org
Abstract: Urban indicator prediction aims to infer socio-economic metrics in diverse urban landscapes using data-driven methods. However, prevalent pre-trained models, particularly those reliant on satellite imagery, face dual challenges. Firstly, concentrating solely on macro-level patterns from satellite data may introduce bias, lacking nuanced details at micro levels, such as architectural details at a place. Secondly, the lack of interpretability in pre-trained models limits their utility in providing transparent evidence for urban planning. In response to these …
abstract arxiv bias challenges cs.ai cs.cv data data-driven diverse economic face foundation foundation model however language macro metrics patterns prediction pre-trained models satellite type urban vision
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