DEEP VIDEO COMPRESSION FOR INTERFRAME CODING

David Alexandre, Hsueh Ming Hang, Wen Hsiao Peng, Marek Domański

研究成果: Conference contribution同行評審

5 引文 斯高帕斯(Scopus)

摘要

A typical learning-based video compression scheme consists of motion coding and residual coding. In this paper, our deep video compression features a motion predictor and refinement networks for interframe coding. To save the bits for transmitting motion information, our scheme performs local motion prediction and sends only the differential motion vectors to the decoder. In the residual coding, we couple the residual decoder with the refine-net to reduce residual signal bits. The experiments show that our work can produce a very competitive coding performance compared to the other learning-based predictive video codecs.

原文English
主出版物標題2021 IEEE International Conference on Image Processing, ICIP 2021 - Proceedings
發行者IEEE Computer Society
頁面2124-2128
頁數5
ISBN(電子)9781665441155
DOIs
出版狀態Published - 2021
事件2021 IEEE International Conference on Image Processing, ICIP 2021 - Anchorage, United States
持續時間: 19 9月 202122 9月 2021

出版系列

名字Proceedings - International Conference on Image Processing, ICIP
2021-September
ISSN(列印)1522-4880

Conference

Conference2021 IEEE International Conference on Image Processing, ICIP 2021
國家/地區United States
城市Anchorage
期間19/09/2122/09/21

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