Traffic flow prediction is important to transportation policy and management. Time-series models based on historical data can hardly reflect non-recurrent events and the impact of multiple factors.

Motivated by the need to improve model performance in traffic monitoring tasks with limited labeled samples, we propose a straightforward augmentation technique tailored for object detection datasets, ...