تقرير
The 6th AI City Challenge
العنوان: | The 6th AI City Challenge |
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المؤلفون: | Naphade, Milind, Wang, Shuo, Anastasiu, David C., Tang, Zheng, Chang, Ming-Ching, Yao, Yue, Zheng, Liang, Rahman, Mohammed Shaiqur, Venkatachalapathy, Archana, Sharma, Anuj, Feng, Qi, Ablavsky, Vitaly, Sclaroff, Stan, Chakraborty, Pranamesh, Li, Alice, Li, Shangru, Chellappa, Rama |
سنة النشر: | 2022 |
المجموعة: | Computer Science |
مصطلحات موضوعية: | Computer Science - Computer Vision and Pattern Recognition |
الوصف: | The 6th edition of the AI City Challenge specifically focuses on problems in two domains where there is tremendous unlocked potential at the intersection of computer vision and artificial intelligence: Intelligent Traffic Systems (ITS), and brick and mortar retail businesses. The four challenge tracks of the 2022 AI City Challenge received participation requests from 254 teams across 27 countries. Track 1 addressed city-scale multi-target multi-camera (MTMC) vehicle tracking. Track 2 addressed natural-language-based vehicle track retrieval. Track 3 was a brand new track for naturalistic driving analysis, where the data were captured by several cameras mounted inside the vehicle focusing on driver safety, and the task was to classify driver actions. Track 4 was another new track aiming to achieve retail store automated checkout using only a single view camera. We released two leader boards for submissions based on different methods, including a public leader board for the contest, where no use of external data is allowed, and a general leader board for all submitted results. The top performance of participating teams established strong baselines and even outperformed the state-of-the-art in the proposed challenge tracks. Comment: Summary of the 6th AI City Challenge Workshop in conjunction with CVPR 2022. arXiv admin note: text overlap with arXiv:2104.12233 |
نوع الوثيقة: | Working Paper |
URL الوصول: | http://arxiv.org/abs/2204.10380 |
رقم الأكسشن: | edsarx.2204.10380 |
قاعدة البيانات: | arXiv |
الوصف غير متاح. |