The 7th AI City Challenge

[Paper] [Website]

Abstract

The AI City Challenge’s seventh edition emphasizes two domains at the intersection of computer vision and artificial intelligence - retail business and Intelligent Traffic Systems (ITS) - that have considerable untapped potential. The 2023 challenge had five tracks, which drew a record-breaking number of participation requests from 508 teams across 46 countries. Track 1 was a brand new track that focused on multi-target multi-camera (MTMC) people tracking, where teams trained and evaluated using both real and highly realistic synthetic data. Track 2 centered around natural-language-based vehicle track retrieval. Track 3 required teams to classify driver actions in naturalistic driving analysis. Track 4 aimed to develop an automated checkout system for retail stores using a single view camera. Track 5, another new addition, tasked teams with detecting violations of the helmet rule for motorcyclists. Two leader boards were released for submissions based on different methods: a public leader board for the contest where external private data wasn’t allowed and a general leader board for all results submitted. The participating teams’ top performances established strong baselines and even outperformed the state-of-the-art in the proposed challenge tracks.

Citation

@inproceedings{Naphade23AICity23,
author = {Milind Naphade and Shuo Wang and David C. Anastasiu and Zheng Tang and Ming-Ching Chang and Yue Yao and Liang Zheng and Mohammed Shaiqur Rahman and Meenakshi S. Arya and Anuj Sharma and Qi Feng and Vitaly Ablavsky and Stan Sclaroff and Pranamesh Chakraborty and Sanjita Prajapati and Alice Li and Shangru Li and Krishna Kunadharaju and Shenxin Jiang and Rama Chellappa},
title = {The 7th {AI} {C}ity {C}hallenge},
booktitle = {Proc. CVPR Workshops},
pages = {5537–5547},
address = {Vancouver, BC, Canada},
year = {2023}
}