Research Labs
All Research Labs
3D Deep Learning
Applied Research
Autonomous Vehicles
Deep Imagination
Publications
AI Playground
New and Featured
AI Art Gallery
NGC Demos
Research Areas
AI & Machine Learning
3D Deep Learning
Computer Vision
Robotics
All Areas
Careers
Academic Collaborations
Government Collaborations
Graduate Fellowship
Internships
Research Openings
Research Scientists
Meet the Team
Licensing
Skip to main content
Artificial Intelligence Computing Leadership from NVIDIA
Login
Research Labs
All Research Labs
3D Deep Learning
Applied Research
Autonomous Vehicles
Deep Imagination
Publications
AI Playground
New and Featured
AI Art Gallery
NGC Demos
Research Areas
AI & Machine Learning
3D Deep Learning
Computer Vision
Robotics
All Areas
Careers
Academic Collaborations
Government Collaborations
Graduate Fellowship
Internships
Research Openings
Research Scientists
Meet the Team
Licensing
Search
Search
Enter the terms you wish to search for.
Publications
CityFlow: A City-Scale Benchmark for Multi-Target Multi-Camera Vehicle Tracking and Re-Identification
CityFlow: A City-Scale Benchmark for Multi-Target Multi-Camera Vehicle Tracking and Re-Identification
Authors
Zheng Tang (University of Washington)
Milind Naphade (NVIDIA)
Ming-Yu Liu
Xiaodong Yang
Stan Birchfield
Shuo Wang (NVIDIA)
Ratnesh Kumar (NVIDIA)
David Anastasiu (San Jose State University)
Jenq-Neng Hwan (University of Washington)
Publication Date
Sunday, June 16, 2019
Published in
CVPR 2019
Research Area
Computer Vision
External Links
arXiv paper
paper on CVPR website
