Corpus ID: 16431768

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 X. Tang},
  journal={ArXiv},
  year={2016},
  volume={abs/1608.02778}
}

• K. Yu, Chao Dong, +1 author X. Tang
• Published 2016
• Computer Science
• ArXiv

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…Expand

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