首页|Video Enhancement Network Based on CNN and Transformer
Video Enhancement Network Based on CNN and Transformer
扫码查看
点击上方二维码区域，可以放大扫码查看
原文链接
万方数据
维普
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.
万方数据
维普
