TY - GEN
T1 - The 6th AI City Challenge
AU - Naphade, Milind
AU - Wang, Shuo
AU - Anastasiu, David C.
AU - Tang, Zheng
AU - Chang, Ming Ching
AU - Yao, Yue
AU - Zheng, Liang
AU - Shaiqur Rahman, Mohammed
AU - Venkatachalapathy, Archana
AU - Sharma, Anuj
AU - Feng, Qi
AU - Ablavsky, Vitaly
AU - Sclaroff, Stan
AU - Chakraborty, Pranamesh
AU - Li, Alice
AU - Li, Shangru
AU - Chellappa, Rama
N1 - Funding Information:
The datasets of the 6th AI City Challenge would not have been possible without significant contributions from the Iowa DOT and an urban traffic agency in the United States. This Challenge was also made possible by significant data curation help from the NVIDIA Corporation and academic partners at the Iowa State University, Boston University, and Australian National University. We would like to specially thank Paul Hendricks and Arman Toorians from the NVIDIA Corporation for their help with the retail dataset.
Publisher Copyright:
© 2022 IEEE.
PY - 2022
Y1 - 2022
N2 - 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.
AB - 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.
UR - http://www.scopus.com/inward/record.url?scp=85129663025&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85129663025&partnerID=8YFLogxK
U2 - 10.1109/CVPRW56347.2022.00378
DO - 10.1109/CVPRW56347.2022.00378
M3 - Conference contribution
AN - SCOPUS:85129663025
T3 - IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops
SP - 3346
EP - 3355
BT - Proceedings - 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops, CVPRW 2022
PB - IEEE Computer Society
T2 - 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops, CVPRW 2022
Y2 - 19 June 2022 through 20 June 2022
ER -