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With the continuous improvement of computing power and deep learningalgorithms in recent years, the foundation model has grown in popularity.Because of its powerful capabilities and excellent performance, this technologyis being adopted and applied by an increasing number of industries. In theintelligent transportation industry, artificial intelligence faces thefollowing typical challenges: few shots, poor generalization, and a lack ofmulti-modal techniques. Foundation model technology can significantly alleviatethe aforementioned issues. To address these, we designed the 1st FoundationModel Challenge, with the goal of increasing the popularity of foundation modeltechnology in traffic scenarios and promoting the rapid development of theintelligent transportation industry. The challenge is divided into two tracks:all-in-one and cross-modal image retrieval. Furthermore, we provide a newbaseline and benchmark for the two tracks, called Open-TransMind. According toour knowledge, Open-TransMind is the first open-source transportationfoundation model with multi-task and multi-modal capabilities. Simultaneously,Open-TransMind can achieve state-of-the-art performance on detection,classification, and segmentation datasets of traffic scenarios. Our source codeis available at https://github.com/Traffic-X/Open-TransMind.

Open-TransMind: A New Baseline and Benchmark for 1st Foundation Model Challenge of Intelligent Transportation