61 citations · 93 across the 5 of their papers we have counts for
5 papers
Spatio-Temporal Graph Neural Point Process for Traffic Congestion Event Prediction
Guangyin Jin, Lingbo Liu, Fuxian Li +1
Traffic congestion event prediction is an important yet challenging task in intelligent transportation systems. Many existing works about traffic prediction integrate various tempo…
Automated Dilated Spatio-Temporal Synchronous Graph Modeling for Traffic Prediction
Guangyin Jin, Fuxian Li, Jinlei Zhang +2
Accurate traffic prediction is a challenging task in intelligent transportation systems because of the complex spatio-temporal dependencies in transportation networks. Many existin…
Dynamic Graph Convolutional Recurrent Network for Traffic Prediction: Benchmark and Solution
Fuxian Li, Jie Feng, Huan Yan +3
Traffic prediction is the cornerstone of an intelligent transportation system. Accurate traffic forecasting is essential for the applications of smart cities, i.e., intelligent tra…
Spatio-Temporal Dual Graph Neural Networks for Travel Time Estimation
Guangyin Jin, Huan Yan, Fuxian Li +2
Travel time estimation is one of the core tasks for the development of intelligent transportation systems. Most previous works model the road segments or intersections separately b…
MV-C3D: A Spatial Correlated Multi-View 3D Convolutional Neural Networks
Qi Xuan, Fuxian Li, Yi Liu +1
As the development of deep neural networks, 3D object recognition is becoming increasingly popular in computer vision community. Many multi-view based methods are proposed to impro…