Video Enhancement Network Based on CNN and Transformer  

作　　者：YUAN Lang HUI Chen WU Yanfeng LIAO Ronghua JIANG Feng GAO Ying 

机构地区：[1]Harbin Institute of Technology,Harbin 150001,China [2]Sichuan University of Science&Engineering,Zigong 643002,China [3]ZTE Corporation,Shenzhen 518057,China

出　　处：《ZTE Communications》2024年第4期78-88,共11页中兴通讯技术（英文版）

基　　金：supported by the Key R&D Program of China under Grant No. 2022YFC3301800;Sichuan Local Technological Development Program under Grant No. 24YRGZN0010;ZTE Industry-University-Institute Cooperation Funds under Grant No. HC-CN-03-2019-12

摘　　要：To enhance the video quality after encoding and decoding in video compression,a video quality enhancement framework is pro-posed based on local and non-local priors in this paper.Low-level features are first extracted through a single convolution layer and then pro-cessed by several conv-tran blocks(CTB)to extract high-level features,which are ultimately transformed into a residual image.The final re-constructed video frame is obtained by performing an element-wise addition of the residual image and the original lossy video frame.Experi-ments show that the proposed Conv-Tran Network(CTN)model effectively recovers the quality loss caused by Versatile Video Coding(VVC)and further improves VVC's performance.

关 键 词：attention fusion mechanism H.266/VVC transformer video coding video quality enhancement 

分 类 号：TP391.41[自动化与计算机技术—计算机应用技术]