Video super-resolution based on spatial-temporal recurrent residual networks.

•A novel deep neural network architecture for video SR.•The first research attempt to incorporate the residual architecture in a deep network to model temporal correlations in video frame sequences for video processing.•The first investigation to unify the spatial convolutional, temporal recurrent and residual architectures into a single deep neural network to solve video SR problems.