This repository implements a deep learning method for video super-resolution using a generative adversarial network with a spatio-temporal discriminator. The approach generates temporally coherent fine details in video sequences by training a generator network to produce high-resolution frames. It was published in ACM Transactions on Graphics and includes inference code, training code, and pre-trained models.