Multi-Level Feature Fusion Network for Lightweight Stereo Image Super-Resolution

arXiv:2405.05497v1 Announce Type: new
Abstract: Stereo image super-resolution utilizes the cross-view complementary information brought by the disparity effect of left and right perspective images to reconstruct higher-quality images. Cascading feature extraction modules and cross-view feature interaction modules to make use of the information from stereo images is the focus of numerous methods. However, this adds a great deal of network parameters and structural redundancy. To facilitate the application of stereo image super-resolution in downstream tasks, we propose an efficient Multi-Level …

arxiv cs.cv feature fusion image network resolution type