The 6th AI City Challenge

TL;DR

The 6th AI City Challenge showcased advancements in computer vision and AI across traffic management and retail, with diverse tracks including vehicle tracking, retrieval, driver action classification, and retail checkout automation, involving 254 teams from 27 countries.

Contribution

This edition introduced four new challenge tracks focusing on multi-camera vehicle tracking, natural language retrieval, driver action analysis, and retail checkout, setting new benchmarks in these domains.

Findings

Top teams established strong baselines.

Outperformed existing state-of-the-art methods.

Demonstrated the potential of AI in smart city applications.

Abstract

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.