Compression Artifacts Removal Using Convolutional Neural Networks

1 code implementation • 2 May 2016 • Pavel Svoboda, Michal Hradis, David Barina, Pavel Zemcik

This paper shows that it is possible to train large and deep convolutional neural networks (CNN) for JPEG compression artifacts reduction, and that such networks can provide significantly better reconstruction quality compared to previously used smaller networks as well as to any other state-of-the-art methods.

CNN for License Plate Motion Deblurring

no code implementations • 25 Feb 2016 • Pavel Svoboda, Michal Hradis, Lukas Marsik, Pavel Zemcik

In this work we explore the previously proposed approach of direct blind deconvolution and denoising with convolutional neural networks in a situation where the blur kernels are partially constrained.

Deblurring Denoising