Automatic Estimation for Visual Quality Changes of Street Space Via Street-View Images and Multimodal Large Language Models Article Swipe

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Hao Liang , Jiaxin Zhang , Yunqin Li , Zehong Zhu , Bowen Wang ·

YOU? · · 2023 · Open Access · · DOI: https://doi.org/10.20944/preprints202311.1473.v1

Estimating Visual Quality of Street Space (VQoSS) is pivotal for urban design, environmental sustainability, civic engagement, etc. Recent advancements, notably in deep learning, have enabled large-scale analysis. However, traditional deep learning approaches are hampered by extensive data annotation requirements and limited adaptability across diverse VQoSS tasks. Multimodal Large Language Models (MLLMs) have recently demonstrated proficiency in various computer vision tasks, positioning them as promising tools for automated VQoSS assessment. In this paper, we pioneer the application of MLLMs to VQoSS change estimation, with our empirical findings affirming their effectiveness. In addition, we introduce Street Quality GPT (SQ-GPT), a model that distills knowledge from the current most powerful but inaccessible (not free) GPT-4, requiring no human efforts. SQ-GPT approaches GPT-4’s performance and is viable for large-scale VQoSS change estimation. In a case study of Nanjin, we showcase the practicality of SQ-GPT and knowledge distillation pipeline. Our work promises to be a valuable asset for future urban studies research.

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Computer science Artificial intelligence Pipeline (software) Machine learning Quality (philosophy) Scale (ratio) Estimation Data science Adaptability Asset (computer security) Sustainability Annotation Deep learning Human–computer interaction Systems engineering Engineering Computer security Cartography Geography Biology Programming language Philosophy Ecology Epistemology

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Type: preprint
Language: en
Landing Page: https://doi.org/10.20944/preprints202311.1473.v1
PDF: https://www.preprints.org/manuscript/202311.1473/v1/download
OA Status: green
Cited By: 2
References: 66
Related Works: 10
OpenAlex ID: https://openalex.org/W4388960531

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DOI: https://doi.org/10.20944/preprints202311.1473.v1

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Title: Automatic Estimation for Visual Quality Changes of Street Space Via Street-View Images and Multimodal Large Language Models

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Type: preprint

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Language: en

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Publication year: 2023

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Publication date: 2023-11-23

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Authors: Hao Liang, Jiaxin Zhang, Yunqin Li, Zehong Zhu, Bowen Wang

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Landing page: https://doi.org/10.20944/preprints202311.1473.v1

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Concepts: Computer science, Artificial intelligence, Pipeline (software), Machine learning, Quality (philosophy), Scale (ratio), Estimation, Data science, Adaptability, Asset (computer security), Sustainability, Annotation, Deep learning, Human–computer interaction, Systems engineering, Engineering, Computer security, Cartography, Geography, Biology, Programming language, Philosophy, Ecology, Epistemology

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Cited by: 2

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