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Learning for Video Compression

Zhibo Chen (陈志波)
Zhibo Chen (陈志波)
Tianyu He
Tianyu He
Xin Jin (金鑫)
Xin Jin (金鑫)
Feng Wu (吴枫)
Feng Wu (吴枫)

IEEE Transactions on Circuits and Systems for Video Technology, pp. 566-576, 2020.

Cited by: 32|Bibtex|Views31|DOI:https://doi.org/10.1109/TCSVT.2019.2892608
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Other Links: dblp.uni-trier.de|academic.microsoft.com|arxiv.org
Keywords:
Image codingVideo compressionSpatiotemporal phenomenaImage reconstructionTransform codingMore(2+)

Abstract:

One key challenge to learning-based video compression is that motion predictive coding, a very effective tool for video compression, can hardly be trained into a neural network. In this paper, we propose the concept of Pixel-MotionCNN (PMCNN) which includes motion extension and hybrid prediction networks. PMCNN can model spatiotemporal co...More

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