FAST LEARNING-BASED SPLIT TYPE PREDICTION ALGORITHM FOR VVC
dc.cclicence | CC-BY-NC | en |
dc.contributor.author | Wang, Dayong | |
dc.contributor.author | Chen, Liulin | |
dc.contributor.author | Lu, Xin | |
dc.contributor.author | Dufaux, Frederic | |
dc.contributor.author | Li, Weisheng | |
dc.contributor.author | Zhu, Ce | |
dc.date.acceptance | 2023-06-21 | |
dc.date.accessioned | 2023-06-26T10:37:43Z | |
dc.date.available | 2023-06-26T10:37:43Z | |
dc.date.issued | 2023-10 | |
dc.description.abstract | As the latest video coding standard, Versatile Video Coding (VVC) is highly efficient at the cost of very high coding com- plexity, which seriously hinders its widespread application. Therefore, it is very crucial to improve its coding speed. In this paper, we propose a learning-based fast split type (ST) prediction algorithm for VVC using a deep learning approach. We first construct a large-scale database containing sufficient STs with diverse video resolution and content. Next, since the ST distributions of coding units (CUs) of different sizes are significantly distinct, so we separately design neural net- works for all different CU sizes. Then, we merge ambiguous STs into four merged classes (MCs) to train models to obtain probabilities of MCs and skip unlikely ones. Experimental results demonstrate that the proposed algorithm can reduce the encoding time of VVC by 67.53% with 1.89% increase in Bjøntegaard delta bit-rate (BDBR) on average. | en |
dc.funder | Other external funder (please detail below) | en |
dc.funder.other | Natural Science Foundation of Chongqing under Grant cstc2020jcyj-msxmX0766 | en |
dc.funder.other | Science and Technology Research Program of Chongqing Municipal Education Com- mission under Grant KJZD-K202100604 | en |
dc.funder.other | Jiangxi Provincial Natural Science Foundation under Grant 20202BABL202006. | en |
dc.identifier.citation | Wang, D., Chen, L., Lu, X., Dufaux, F., Li, W. and Zhu, C. (2023) FAST LEARNING-BASED SPLIT TYPE PREDICTION ALGORITHM FOR VVC. IEEE International Conference on Image Processing (ICIP) | en |
dc.identifier.uri | https://hdl.handle.net/2086/23038 | |
dc.language.iso | en | en |
dc.peerreviewed | Yes | en |
dc.publisher | IEEE | en |
dc.researchinstitute | Institute of Artificial Intelligence (IAI) | en |
dc.subject | VVC | en |
dc.subject | split type | en |
dc.subject | deep learning | en |
dc.title | FAST LEARNING-BASED SPLIT TYPE PREDICTION ALGORITHM FOR VVC | en |
dc.type | Conference | en |