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IBVC: Interpolation-driven B-frame video compression

delete2024-09-01
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OA
AI
C
Chenming Xu
刘
刘美琴 (Meiqin Liu) *
姚
姚超 (Chao Yao)
W
Weisi Lin
赵
赵耀 (Yao Zhao)
DOI:10.1016/j.patcog.2024.110465delete
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摘要

摘要

En 中文
Learned B-frame video compression aims to adopt bi-directional motion estimation and motion compensation (MEMC) coding for middle frame reconstruction. However, previous learned approaches often directly extend neural P-frame codecs to B-frame relying on bi-directional optical-flow estimation or video frame interpolation. They suffer from inaccurate quantized motions and inefficient motion compensation. To address these issues, we propose a simple yet effective structure called Interpolation-driven B-frame Video Compression (IBVC). Our approach only involves two major operations: video frame interpolation and artifact reduction compression. IBVC introduces a bit-rate free MEMC based on interpolation, which avoids optical-flow quantization and additional compression distortions. Later, to reduce duplicate bit-rate consumption and focus on unaligned artifacts, a residual guided masking encoder is deployed to adaptively select the meaningful contexts with interpolated multi-scale dependencies. In addition, a conditional spatio-temporal decoder is proposed to eliminate location errors and artifacts instead of using MEMC coding in other methods. The experimental results on B-frame coding demonstrate that IBVC has significant improvements compared to the relevant state-of-theart methods. Meanwhile, our approach can save bit rates compared with the random access (RA) configuration of H.266 (VTM). The code will be available at https://github.com/ruhig6/IBVC.
Keyword:
Learned video compression
Video frame interpolation
Artifact reduction
Bi-directional motion compensation
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期刊

Pattern Recognition 封面图
Pattern Recognition
IF:
7.6
论文数:
1.3W
被引数:
4.5W

机构

B
Beijing Jiaotong University
学者数:
2.2W
论文数: 1.7W
被引数: 1.2W
N
Nanyang Technological University
学者数:
4.9W
论文数: 4.8W
被引数: 8.1W
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