改进视频编码中的亚像素运动补偿，提升压缩效率并降低解码开销。
Efficient Sub-pixel Motion Compensation in Learned Video Codecs
- 借鉴传统编码器设计更优插值滤波与分块运动信息
- 实现比特率下降超10%，解码复杂度降低45%
- 适合关注视频编码压缩性能与效率的研究者
运动补偿是视频编码的核心组件。传统编码标准（如HEVC和VVC）对亚像素运动补偿进行了精细优化，而学习型编码器通常仅使用简单的双线性滤波。本文受传统方法启发，提出通过采用更先进的插值滤波、基于块的运动信息及有限运动精度来改进学习型编码器的运动补偿。在Cool-chic编码器上的实验表明，该方法可使码率降低超过10%，同时将运动相关解码复杂度从每像素391个乘加运算降至214个。所有代码已开源于https://github.com/Orange-OpenSource/Cool-Chic。
原文摘要 · Abstract (English)
Motion compensation is a key component of video codecs. Conventional codecs (HEVC and VVC) have carefully refined this coding step, with an important focus on sub-pixel motion compensation. On the other hand, learned codecs achieve sub-pixel motion compensation through simple bilinear filtering. This paper offers to improve learned codec motion compensation by drawing inspiration from conventional codecs. It is shown that the usage of more advanced interpolation filters, block-based motion information and finite motion accuracy lead to better compression performance and lower decoding complexity. Experimental results are provided on the Cool-chic video codec, where we demonstrate a rate decrease of more than 10% and a lowering of motion-related decoding complexity from 391 MAC per pixel to 214 MAC per pixel. All contributions are made open-source at https://github.com/Orange-OpenSource/Cool-Chic
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