"Disparity-aware domain adaptation in stereo image restoration" by Bo YAN, Chenxi MA et al.
 

Publication Type

Conference Proceeding Article

Version

publishedVersion

Publication Date

6-2020

Abstract

Under stereo settings, the problems of disparity estimation, stereo magnification and stereo-view synthesis have gathered wide attention. However, the limited image quality brings non-negligible difficulties in developing related applications and becomes the main bottleneck of stereo images. To the best of our knowledge, stereo image restoration is rarely studied. Towards this end, this paper analyses how to effectively explore disparity information, and proposes a unified stereo image restoration framework. The proposed framework explicitly learn the inherent pixel correspondence between stereo views and restores stereo image with the cross-view information at image and feature level. A Feature Modulation Dense Block (FMDB) is introduced to insert disparity prior throughout the whole network. The experiments in terms of efficiency, objective and perceptual quality, and the accuracy of depth estimation demonstrates the superiority of the proposed framework on various stereo image restoration tasks.

Keywords

image restoration, Image reconstruction, Feature extraction, Modulation, Estimation, Task analysis, Imaging

Discipline

Graphics and Human Computer Interfaces

Research Areas

Data Science and Engineering

Publication

Proceedings of the 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), Seattle, June 13-19

First Page

13181

Last Page

13187

ISBN

9781728171685

Identifier

10.1109/CVPR42600.2020.01319

Publisher

IEEE

City or Country

Los Alamitos, CA

Additional URL

http://doi.org/10.1109/CVPR42600.2020.01319

Download

Share

COinS