Academy & Industry Research Collaboration Center (AIRCC)

Volume 9, Number 2, February 2019

In-Vehicle Camera Images Prediction by Generative Adversarial Network


Junta Watanabe and Tad Gonsalves, Sophia University, Japan


Moving object detection is one of the fundamental technologies necessary to realize autonomous driving. In this study, we propose the prediction of an in-vehicle camera image by Generative Adversarial Network (GAN). From the past images input to the system, it predicts the future images at the output. By predicting the motion of a moving object, it can predict the destination of the moving object. The proposed model can predict the motion of moving objects such as cars, bicycles, and pedestrians.


Deep Learning, Image Processing, Convolutional Neural Network, GAN, DGAN