Deep Convolution Networks for Compression Artifacts Reduction
@article{Yu2016DeepCN, title={Deep Convolution Networks for Compression Artifacts Reduction}, author={K. Yu and Chao Dong and Chen Change Loy and Xiaoou Tang}, journal={ArXiv}, year={2016}, volume={abs/1608.02778} }
Lossy compression introduces complex compression artifacts, particularly blocking artifacts, ringing effects and blurring. [] Key Method To meet the speed requirement of real-world applications, we further accelerate the proposed baseline model by layer decomposition and joint use of large-stride convolutional and deconvolutional layers. This also leads to a more general CNN framework that has a close relationship with the conventional Multi-Layer Perceptron (MLP). Finally, the modified network achieves a…
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