A fast CU partition algorithm of ERP 360‐degree video based on deep learning
Hai Xiang, Fen Chen, Zongju Peng, Lian Huang · Electronics Letters · 2025
Abstract This article proposes a deep‐learning‐based fast coding unit (CU) partition algorithm to reduce encoding time of equirectangular projection (ERP) 360‐degree videos in versatile video coding. First, an ERP 360‐degree dataset with ERP latitude characteristics and quantitative parameter characteristics is established. Then, a lightweight prediction partition convolutional neural network is designed to predict the partition probability of 44 CU edges in 3232 luminance CU. Finally, an intra prediction decision‐making scheme is developed to reduce the number of candidate modes of CUs with size equal to or smaller than 3232, thereby achieving fast encoding. Experimental results show that the proposed method saves 58.51% of encoding time in All Intra configuration and only increases Bjontegaard delta bit‐rate by 1.39%.