An Efficient QP Variable Convolutional Neural Network Based In-loop Filter for Intra Coding

2021 Data Compression Conference (DCC)(2021)

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摘要
In this paper, a novel QP variable convolutional neural network based in-loop filter is proposed for VVC intra coding. To avoid training and deploying multiple networks, we develop an efficient QP attention module (QPAM) which can capture compression noise levels for different QPs and emphasize meaningful features along channel dimension. Then we embed QPAM into the residual block, and based on it...
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关键词
Training,Data compression,Mean square error methods,Network architecture,Controllability,Encoding,Convolutional neural networks
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