Novel Coding Tools Based on Characteristics for Short Videos

Zhihao Zhang, Xiangyu Lin, Daowen Li, Jue Mao, Yaqing Pan, Yuxiang Liu, Lu Yu
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Abstract

Currently, short videos occupy large proportion of live streaming media and short video coding attracts intense attention. Different from traditional online videos, short videos feature frequent scene switching and allow various complex special effects to be added. For the unique characteristics of these short videos, we proposed an advanced video compression platform, which includes Library Picture based Cross Random Access Point Reference (LP-CRAPR), Affine-based Intra Block Copy (AIBC) and Local Illumination Compensation (LIC), to meet the challenges of short video coding. The experimental results show that our proposed platform has performed 5.84% and 2.74% gain under Random Access (RA) and All Intra (AI) configuration compared to VTM 4.0, with approximately two times encoding complexity increasing and no additional decoding time. For our proposed short video coding, high coding efficiency and improved subjective results are achieved.
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基于短视频特征的新型编码工具
目前,短视频在直播媒体中占有很大的比重,短视频编码备受关注。与传统的网络视频不同,短视频的特点是场景切换频繁,可以添加各种复杂的特效。针对短视频的特点,提出了一种基于库图交叉随机接入点参考(LP-CRAPR)、仿射块内复制(AIBC)和局部光照补偿(LIC)的视频压缩平台,以应对短视频编码的挑战。实验结果表明,与VTM 4.0相比,我们提出的平台在随机接入(RA)和全内网(AI)配置下分别获得了5.84%和2.74%的增益,编码复杂度提高了约2倍,且没有增加解码时间。对于我们提出的短视频编码,实现了较高的编码效率和较好的主观效果。
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