2020 AI CITY CHALLENGE

Transportation is one of the largest segments that can benefit from actionable insights derived from data captured by sensors. Between traffic , signaling systems, transportation systems, infrastructure, and transit, the opportunity for insights from these sensors to make transportation systems smarter is immense. Unfortunately, there are several reasons why these potential benefits have not yet materialized. Poor data quality, the lack of labels for the data, and the lack of high-quality models that can convert the data into actionable insights are some of the biggest impediments to unlocking the value of the data. There is also need for platforms that allow for appropriate analysis from edge to cloud, which will accelerate the development and deployment of these models. The AI City Workshop at CVPR 2020 will specifically focus on ITS problems such as:

  • Turn-counts used by DOTs for signal timing planning
  • City-scale multi-camera vehicle re-identification w. real and synthetic trianing data
  • City-scale multi-camera vehicle tracking
  • Anomaly detection – detecting anomalies such as lane violation, wrong-direction driving, etc.

We solicit original contributions in these and related areas where computer vision and specifically deep learning have shown promise in achieving large-scale practical deployment that will help make cities smarter.

To accelerate the research and development of techniques, the 4th edition of this Challenge will push the research and development in two new ways, First, the challenge will introduce a track that not only measures effectiveness on tasks that are relevant to DOTs but also measures the efficiency of completing these tasks and the ability of systems to operate in real-time. To our knowledge, this will be the first such challenge that combines effectiveness and efficiency evaluation of tasks needs by DOTs for operational deployments of these systems. The second change in this edition will be the introduction of augmented synthetic data for the purpose of substantially increasing the training set for the task of re-identification.

TENTATIVE AGENDA

CVPR 2020 at The Washington State Convention Center in Seattle, WA

09:00 – 09:15

Workshop Kickoff and Opening Comments

09:15 – 09:45

First Keynote Speech

09:45 – 10:00

Coffee Break

10:00 – 12:00

Six Oral presentations (20 minutes each)

12:00 – 13:00

Lunch

13:00 – 13:30

Second Keynote Speech

13:30 – 15:30

Six Oral presentations (20 minutes each)

15:30 – 16:00

Break

16:00 – 16:30

Announcement of Challenge Winners and Awards Ceremony

16:30 – 17:30

Reception

ORGANIZING COMMITTEE

Milind Naphade

NVIDIA Corporation

Rama Chellappa

University of Maryland, College Park

David Anastasiu

San Jose State University

Anuj Sharma

Iowa State University

Ming-Ching Chang

University at Albany – SUNY

Xiaodong Yang

NVIDIA Research

Shuo Wang

NVIDIA Corporation

Zheng Tang

Amazon