In recent years, with the rise of various online learning platforms and game live broadcast industries, screen content video, a special type of video, is gradually emerging, and its traffic on the Internet is also increasing. Therefore, how to effectively enhance the quality of the screen content video has become an urgent problem to be solved. There exist a few successful compressed video enhancement algorithms. However, since there are a large number of areas with similar colors in the compressed screen content video, the traditional algorithms based on optical flow and deformable convolution cannot align the screen content video frames well. Specifically, for screen content videos containing animations and games, we propose a screen content video quality enhancement network based on the cross-fusion of multi-frame information. It includes a feature extraction module, a feature fusion module, an edge detail recovery module, and a reconstruction module. Our main contribution is the alignment-free quality enhancement framework based on cross-frame information fusion instead of traditional alignment based approaches. Through our experiments, the best results have been achieved on 13 screen content videos containing animations and games compressed by the SCC branch of HEVC/H.265.