Multiple classifier-based fast coding unit partition for intra coding in future video coding-Reference-Cited by-同舟云学术

Multiple classifier-based fast coding unit partition for intra coding in future video coding

Published:2019-10 Issue: Volume:78 Page:171-179
ISSN:0923-5965
Container-title:Signal Processing: Image Communication
language:en
Short-container-title:Signal Processing: Image Communication

Author:

Peng Zongju,Huang Chao^ORCID,Chen Fen,Jiang Gangyi,Cui Xin,Yu Mei

Funder

National Natural Science Foundation of China

Natural Science Foundation of Zhejiang Province, China

K. C. Wong Magna Fund in Ningbo University

Publisher

Elsevier BV

Subject

Electrical and Electronic Engineering,Computer Vision and Pattern Recognition,Signal Processing,Software

Reference37 articles.

1. Overview of the high efficiency video coding (HEVC) standard;Sullivan;IEEE Trans. Circuits Syst. Video Technol.,2012

2. Recent advances in omnidirectional video coding for virtual reality: Projection and evaluation;Chen;Signal Process.,2018

3. Possibility distribution based lossless coding and its optimization;He;Signal Process.,2018

4. Possibility distribution based lossless coding and its optimization;Wang;Signal Process.,2015

5. J. Chen, X. Li, F. Zou, M. Karczewicz, W. Chien, T. Hsieh, Performance evaluation of JEM 1 tools by Qualcomm, Joint Video Exploration Team (JVET), doc. JVET-B0045, Feb. 2016.

Cited by 10 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Neural texture transfer assisted video coding with adaptive up-sampling;Signal Processing: Image Communication;2022-09

2. Attention-based framework for weakly supervised video anomaly detection;The Journal of Supercomputing;2022-01-10

3. Efficient Partition Decision Based on Visual Perception and Machine Learning for H.266/Versatile Video Coding;IEEE Access;2022

4. Temporal-Aware Self-Supervised Learning for Unsupervised Video Anomaly Detection;2021 5th Asian Conference on Artificial Intelligence Technology (ACAIT);2021-10-29

5. VVC partitioning decision driven by machine learning for a comprehensive hardware encoder;2021 IEEE 23rd International Workshop on Multimedia Signal Processing (MMSP);2021-10-06