1 citations · 1 across the 3 of their papers we have counts for
6 papers
The 10th AI City Challenge
Zheng Tang, Shuo Wang, David C. Anastasiu +34
The 10th AI City Challenge, held with ECCV 2026, marks a decade of community benchmarking for intelligent transportation, smart cities, and physical AI. Since its 2017 start with v…
The 7th AI City Challenge
Milind Naphade, Shuo Wang, David C. Anastasiu +17
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…
Driver Maneuver Detection and Analysis using Time Series Segmentation and Classification
Armstrong Aboah, Yaw Adu-Gyamfi, Senem Velipasalar Gursoy +3
The current paper implements a methodology for automatically detecting vehicle maneuvers from vehicle telemetry data under naturalistic driving settings. Previous approaches have t…
Synthetic Distracted Driving (SynDD2) dataset for analyzing distracted behaviors and various gaze zones of a driver
Mohammed Shaiqur Rahman, Jiyang Wang, Senem Velipasalar Gursoy +3
This article presents a synthetic distracted driving (SynDD2 - a continuum of SynDD1) dataset for machine learning models to detect and analyze drivers' various distracted behavior…
The 5th AI City Challenge
Milind Naphade, Shuo Wang, David C. Anastasiu +11
The AI City Challenge was created with two goals in mind: (1) pushing the boundaries of research and development in intelligent video analysis for smarter cities use cases, and (2)…
The 4th AI City Challenge
Milind Naphade, Shuo Wang, David Anastasiu +7
The AI City Challenge was created to accelerate intelligent video analysis that helps make cities smarter and safer. Transportation is one of the largest segments that can benefit…