CVPR 2023 – Better “CMOS” Produces Clearer Images:

In this episode we discuss Better “CMOS” Produces Clearer Images:
by Xuhai Chen, Jiangning Zhang, Chao Xu, Yabiao Wang, Chengjie Wang, Yong Liu. The paper discusses the problem of space-variant blur in blind image super-resolution methods, which severely affects their performance. To tackle this issue, the authors introduce two new datasets and design a Cross-MOdal fuSion network (CMOS) that estimates both blur and semantics simultaneously. The CMOS incorporates a feature Grouping Interac-tive Attention (GIA) module to make the two modalities interact effectively and avoid inconsistency. The experiments demonstrate the superiority of their method in terms of quantitative metrics like PSNR/SSIM.