Paper Info
Title
Effective Object Detection From Traffic Camera Videos
Abstract
The Nvidia AI City Challenge[1] is a recent effort to materialize the potential benefits of actionable insights in current traffic systems by utilizing both large amount of richly annotated traffic camera video data captured by growing number of cameras, and advanced technologies developed in recent years in image and video recognition and analysis. In this work, we will compare the AI City dataset with other existing vehicle detection datasets, and illustrate the details of the solution of our winning entries to the 1st Nvidia AI City Challenge. Our code and models are also available at https://github.com/NVIDIAAICITYCHALLENGE/AICity_Team24.
Year
Venue
Keywords
2017
2017 IEEE SMARTWORLD, UBIQUITOUS INTELLIGENCE & COMPUTING, ADVANCED & TRUSTED COMPUTED, SCALABLE COMPUTING & COMMUNICATIONS, CLOUD & BIG DATA COMPUTING, INTERNET OF PEOPLE AND SMART CITY INNOVATION (SMARTWORLD/SCALCOM/UIC/ATC/CBDCOM/IOP/SCI)
Object detection, vehicle detection, pedestrian detection, traffic light detection, traffic cameras, video analysis
Field
DocType
Citations 
Object detection,Computer science,Traffic camera,Computer network,Real-time computing,Vehicle detection,Pedestrian detection
Conference
0
PageRank 
References 
Authors
0.34
10
5
Name
Order
Citations
PageRank
Honghui Shi118320.24
Zhichao Liu28510.41
Yuchen Fan333217.14
Xinchao Wang447443.70
Thomas S. Huang5278152618.42