The Versatile Video Coding (VVC) achieves superior coding efficiency as compared with the High Efficiency Video Coding (HEVC), while its excellent coding performance is at the cost of several high computational complexity coding tools, such as Quad-Tree plus Multi-type Tree (QTMT)-based Coding Units (CUs) and multiple inter prediction modes. To reduce the computational complexity of VVC, a CNN-based fast inter coding method is proposed in this paper. First, a multi-information fusion CNN (MF-CNN) model is proposed to early terminate the QTMT-based CU partition process by jointly using the multi-domain information. Then, a content complexity-based early Merge mode decision is proposed to skip the time-consuming inter prediction modes by considering the CU prediction residuals and the confidence of MF-CNN. Experimental results show that the proposed method reduces an average of 30.63% VVC encoding time, and the Bjøontegaard Delta Bit Rate (BDBR) increases about 3%.

中文翻译：

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一种基于CNN的VVC快速帧间编码方法

与高效视频编码 (HEVC) 相比，通用视频编码 (VVC) 实现了更高的编码效率，而其出色的编码性能是以使用几种高计算复杂度的编码工具为代价的，例如 Quad-Tree plus Multi-type Tree (QTMT) 基于编码单元 (CU) 和多种帧间预测模式。为了降低VVC的计算复杂度，本文提出了一种基于CNN的快速帧间编码方法。首先，提出了一种多信息融合CNN（MF-CNN）模型，通过联合使用多域信息来提前终止基于QTMT的CU划分过程。然后，通过考虑 CU 预测残差和 MF-CNN 的置信度，提出了一种基于内容复杂度的早期合并模式决策，以跳过耗时的帧间预测模式。