A large number of camera are installed in the campus. Vehicle tracking can be done in campus camera network. Reliable vehicle recognition from videos can provide statistical information for traffic monitoring and predictions. For such information to be useful, recognition should be done in real-time at an acceptable accuracy. Inspired by recent developments on deep-learning based object detection methods, this research attempts to apply convolutional neural networks to vehicle recognition from videos.