Advancing Object Detection in Transportation with Multimodal Large Language Models (MLLMs): A Comprehensive Review and Empirical Testing

Advancing Object Detection in Transportation with Multimodal Large Language Models (MLLMs): A Comprehensive Review and Empirical Testing

This study aims to comprehensively review and empirically evaluate the application of multimodal large language models (MLLMs) and Large Vision Models (VLMs) in object detection for transportation systems. In the first fold, we provide a background about the potential benefits of MLLMs in transporta...

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Bibliographic Details
Main Authors: Huthaifa I. Ashqar, Ahmed Jaber, Taqwa I. Alhadidi, Mohammed Elhenawy
Format: Article
Language:English
Published: MDPI AG 2025-06-01
Series:Computation
Subjects:
multimodal large language models (MLLMs)
end-to-end object detection
large vision models (VLMs)
autonomous driving
intelligent transportation systems (ITS)
Online Access:https://www.mdpi.com/2079-3197/13/6/133
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