computer-vision-5

Image Compression Artifact Reduction

3260 papers • 126 benchmarks • 313 datasets

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Most implemented papers

Residual Dense Network for Image Restoration

Yapeng Tian, Yu Kong, Y. Fu, Yulun Zhang, Bineng Zhong•Mon Dec 24 2018

This work proposes residual dense block (RDB) to extract abundant local features via densely connected convolutional layers and proposes local feature fusion in RDB to adaptively learn more effective features from preceding and current local features and stabilize the training of wider network.

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Towards Flexible Blind JPEG Artifacts Removal

K. Zhang, Radu Timofte, Jiaxi Jiang•Tue Sep 28 2021

This paper proposes a flexible blind convolutional neural network that can predict the adjustable quality factor to control the trade-off between artifacts removal and details preservation and achieves favorable performance against state-of-the-art methods in terms of both quantitative metrics and visual quality.

136 0

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