Graph Convolutional Adversarial Networks for Spatiotemporal Anomaly Detection

Graph Convolutional Adversarial Networks for Spatiotemporal Anomaly Detection is a research paper that proposes a new approach to detect anomalies in spatiotemporal data using graph convolutional networks and adversarial training. The proposed model shows promising results in detecting anomalies in traffic flow and video surveillance datasets.