JVET 신경망 기반 비디오코딩

Neural Network based Video Coding in JVET

초록

After the Versatile Video Coding (VVC)/H.266 standard was completed, the Joint Video Exploration Team (JVET) began to investigate new technologies that could significantly increase coding gain for the next generation video coding standard. One direction is to investigate signal processing based tools, while the other is to investigate Neural Network based technology. Neural Network based Video Coding (NNVC) has not been studied previously, and this is the first trial of such an approach in the standard group. After two years of research, JVET produced the first common software called Neural Compression Software (NCS) with two NN-based in-loop filtering tools at the 27th meeting and began to maintain NN-based technologies for the common experiment. The coding performances of the two filters in NCS-1.0 are shown to be 8.71% and 9.44% on average in a random access scenario, respectively. All the material related to NCS can be found in the repository of the JVET. In this paper, we provide a brief overview and review of the NNVC activity studied in JVET in order to provide trend and insight for the new direction of video coding standard.

키워드

NNVCJVETNN based video coding
제목
JVET 신경망 기반 비디오코딩
제목 (타언어)
Neural Network based Video Coding in JVET
저자
최기호
DOI
10.5909/JBE.2022.27.7.1021
발행일
2022-12
저널명
방송공학회 논문지
27
7
페이지
1021 ~ 1033