Inferring intersection traffic patterns with sparse video surveillance information: An st-gan method
Traffic patterns of urban road intersections are important in traffic monitoring and accident
prediction, thus play crucial roles in urban traffic management. Although real-time traffic …
prediction, thus play crucial roles in urban traffic management. Although real-time traffic …
Curb-gan: Conditional urban traffic estimation through spatio-temporal generative adversarial networks
Given an urban development plan and the historical traffic observations over the road
network, the Conditional Urban Traffic Estimation problem aims to estimate the resulting …
network, the Conditional Urban Traffic Estimation problem aims to estimate the resulting …
[PDF][PDF] Real-time Traffic Pattern Analysis and Inference with Sparse Video Surveillance Information.
Y Wang, Y Xiao, X Xie, R Chen, H Liu - IJCAI, 2018 - ijcai.org
Recent advances in video surveillance systems enable a new paradigm for intelligent urban
traffic management systems. Since surveillance cameras are usually sparsely located to …
traffic management systems. Since surveillance cameras are usually sparsely located to …
Dynamic multi-view graph neural networks for citywide traffic inference
Accurate citywide traffic inference is critical for improving intelligent transportation systems
with smart city applications. However, this task is very challenging given the limited training …
with smart city applications. However, this task is very challenging given the limited training …
Network-wide traffic state reconstruction: An integrated generative adversarial network framework with structural deep network embedding
Traffic data imputation plays a crucial role in Intelligent Transportation System (ITS)
applications when handling missing data. Previous methods have primarily focused on …
applications when handling missing data. Previous methods have primarily focused on …
Trajnet: A trajectory-based deep learning model for traffic prediction
Ridesharing companies such as Ube and DiDi provide ride-hailing services where
passengers and drivers are matched via mobile apps. As a result, large amounts of vehicle …
passengers and drivers are matched via mobile apps. As a result, large amounts of vehicle …
Graph convolutional adversarial networks for spatiotemporal anomaly detection
Traffic anomalies, such as traffic accidents and unexpected crowd gathering, may endanger
public safety if not handled timely. Detecting traffic anomalies in their early stage can benefit …
public safety if not handled timely. Detecting traffic anomalies in their early stage can benefit …
Strans-gan: Spatially-transferable generative adversarial networks for urban traffic estimation
Conditional traffic estimation is a vital problem in urban plan deployment, which can help
evaluate urban construction plans and improve transportation efficiency. Conventional …
evaluate urban construction plans and improve transportation efficiency. Conventional …
C3-GAN: Complex-Condition-Controlled Urban Traffic Estimation through Generative Adversarial Networks
Given historical traffic distributions and associated urban conditions observed in a city, the
conditional urban traffic estimation problem aims at estimating realistic future projections of …
conditional urban traffic estimation problem aims at estimating realistic future projections of …
Trafficgan: Network-scale deep traffic prediction with generative adversarial nets
Traffic flow prediction has received rising research interest recently since it is a key step to
prevent and relieve traffic congestion in urban areas. Existing methods mostly focus on road …
prevent and relieve traffic congestion in urban areas. Existing methods mostly focus on road …