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http://dx.doi.org/10.5909/JBE.2021.26.5.652

Motion Vector Resolution Decision Algorithm based on Neural Network for Fast VVC Encoding  

Baek, Han-gyul (School of Computer Science and Engineering, Kyungpook National University)
Park, Sang-hyo (School of Computer Science and Engineering, Kyungpook National University)
Publication Information
Journal of Broadcast Engineering / v.26, no.5, 2021 , pp. 652-655 More about this Journal
Abstract
Among various inter prediction techniques of Versatile Video Coding (VVC), adaptive motion vector resolution (AMVR) technology has been adopted. However, for AMVR, various MVs should be tested per each coding unit, which needs a computation of rate-distortion cost and results in an increase in encoding complexity. Therefore, in order to reduce the encoding complexity of AMVR, it is necessary to effectively find an optimal AMVR mode. In this paper, we propose a lightweight neural network-based AMVR decision algorithm based on more diverse datasets.
Keywords
VVC; inter prediction; motion vector resolution; encoding complexity; Multi-layer perceptron;
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