arXiv Open Access 2023

The 7th AI City Challenge

Milind Naphade Shuo Wang David C. Anastasiu Zheng Tang Ming-Ching Chang +15 lainnya
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Abstrak

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.

Topik & Kata Kunci

Penulis (20)

M

Milind Naphade

S

Shuo Wang

D

David C. Anastasiu

Z

Zheng Tang

M

Ming-Ching Chang

Y

Yue Yao

L

Liang Zheng

M

Mohammed Shaiqur Rahman

M

Meenakshi S. Arya

A

Anuj Sharma

Q

Qi Feng

V

Vitaly Ablavsky

S

Stan Sclaroff

P

Pranamesh Chakraborty

S

Sanjita Prajapati

A

Alice Li

S

Shangru Li

K

Krishna Kunadharaju

S

Shenxin Jiang

R

Rama Chellappa

Format Sitasi

Naphade, M., Wang, S., Anastasiu, D.C., Tang, Z., Chang, M., Yao, Y. et al. (2023). The 7th AI City Challenge. https://arxiv.org/abs/2304.07500

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2023
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en
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arXiv
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Open Access ✓