Disparity-Aware Domain Adaptation in Stereo Image Restoration

Bo Yan, Chenxi Ma, Bahetiyaer Bare, Weimin Tan, Steven C. H. Hoi; Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2020, pp. 13179-13187


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.

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author = {Yan, Bo and Ma, Chenxi and Bare, Bahetiyaer and Tan, Weimin and Hoi, Steven C. H.},
title = {Disparity-Aware Domain Adaptation in Stereo Image Restoration},
booktitle = {Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
month = {June},
year = {2020}