  In this paper, we address the problem of blind deblurring with high
efficiency. We propose a set of lightweight deep-wiener-network to finish the
task with real-time speed. The Network contains a deep neural network for
estimating parameters of wiener networks and a wiener network for deblurring.
Experimental evaluations show that our approaches have an edge on State of the
Art in terms of inference times and numbers of parameters. Two of our models
can reach a speed of 100 images per second, which is qualified for real-time
deblurring. Further research may focus on some real-world applications of
deblurring with our models.
