3 citations · 4 across the 2 of their papers we have counts for
4 papers
STG4Traffic: A Survey and Benchmark of Spatial-Temporal Graph Neural Networks for Traffic Prediction
Xunlian Luo, Chunjiang Zhu, Detian Zhang +1
Traffic prediction has been an active research topic in the domain of spatial-temporal data mining. Accurate real-time traffic prediction is essential to improve the safety, stabil…
Attention-based Spatial-Temporal Graph Convolutional Recurrent Networks for Traffic Forecasting
Haiyang Liu, Chunjiang Zhu, Detian Zhang +1
Traffic forecasting is one of the most fundamental problems in transportation science and artificial intelligence. The key challenge is to effectively model complex spatial-tempora…
Dynamic Graph Convolutional Network with Attention Fusion for Traffic Flow Prediction
Xunlian Luo, Chunjiang Zhu, Detian Zhang +1
Accurate and real-time traffic state prediction is of great practical importance for urban traffic control and web mapping services. With the support of massive data, deep learning…
Multi Scale Temporal Graph Networks For Skeleton-based Action Recognition
Tingwei Li, Ruiwen Zhang, Qing Li
Graph convolutional networks (GCNs) can effectively capture the features of related nodes and improve the performance of the model. More attention is paid to employing GCN in Skele…