High-Efficiency Video Coding (HEVC) surpasses its predecessors in encoding efficiency by introducing new coding tools at the cost of an increased encoding time-complexity. The Coding Tree Unit (CTU) is the main building block used in HEVC. In the HEVC standard, frames are divided into CTUs with the predetermined size of up to 64x64 pixels. Each CTU is then divided recursively into a number of equally sized square areas, known as Coding Units (CUs). Although this diversity of frame partitioning increases encoding efficiency, it also causes an increase in the time complexity due to the increased number of ways to find the optimal partitioning. To address this complexity, numerous algorithms have been proposed to eliminate unnecessary searches during partitioning CTUs by exploiting the correlation in the video. In this paper, existing CTU depth decision algorithms for HEVC are surveyed. These algorithms are categorized into two groups, namely statistics and machine learning approaches. Statistics approaches are further subdivided into neighboring and inherent approaches. Neighboring approaches exploit the similarity between adjacent CTUs to limit the depth range of the current CTU, while inherent approaches use only the available information within the current CTU. Machine learning approaches try to extract and exploit similarities implicitly. Traditional methods like support vector machines or random forests use manually selected features, while recently proposed deep learning methods extract features during training. Finally, this paper discusses extending these methods to more recent video coding formats such as Versatile Video Coding (VVC) and AOMedia Video 1(AV1).

翻译：高效益视频编码(HEVC) 超越了编码效率的前身, 采用了新的编码工具, 成本增加了编码时间复杂性。 编码树股(CTU)是HEVC使用的主要构件块。 在 HEVC 标准中, 框架被分为CTU, 其预定大小为64x64 像素。 然后将每个CTU相继分为若干同样大小的平方块, 称为编码单位( CUs ) 。 虽然这种框架分割方式的多样性提高了编码效率, 但它也增加了时间复杂性, 但由于寻找最佳分区法的方法越来越多, 也增加了时间复杂性。 为解决这一复杂性, 提出了许多算法, 通过利用视频中的关联性来消除在分区化 CTU中不必要的搜索。 本文中, 现有的CTU深度决定算法被重新分为两个组, 即统计和机器学习方法。 统计方法被进一步细分为邻接和内在方法。 与相近处的方法相似, 接近的方法利用了类似于CTUC的视频格式, 与最近的一些内路路路路路路段, 学习方法, 。 逐步利用这些精选的C 学习方法。