Beyond Monocular Deraining: Stereo Image Deraining via Semantic Understanding

Kaihao Zhang, Wenhan Luo, Wenqi Ren*, Jingwen Wang, Fang Zhao, Lin Ma, Hongdong Li

*Corresponding author for this work

    Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

    28 Citations (Scopus)

    Abstract

    Rain is a common natural phenomenon. Taking images in the rain however often results in degraded quality of images, thus compromises the performance of many computer vision systems. Most existing de-rain algorithms use only one single input image and aim to recover a clean image. Few work has exploited stereo images. Moreover, even for single image based monocular deraining, many current methods fail to complete the task satisfactorily because they mostly rely on per pixel loss functions and ignore semantic information. In this paper, we present a Paired Rain Removal Network (PRRNet), which exploits both stereo images and semantic information. Specifically, we develop a Semantic-Aware Deraining Module (SADM) which solves both tasks of semantic segmentation and deraining of scenes, and a Semantic-Fusion Network (SFNet) and a View-Fusion Network (VFNet) which fuse semantic information and multi-view information respectively. We also propose new stereo based rainy datasets for benchmarking. Experiments on both monocular and the newly proposed stereo rainy datasets demonstrate that the proposed method achieves the state-of-the-art performance.

    Original languageEnglish
    Title of host publicationComputer Vision – ECCV 2020 - 16th European Conference, 2020, Proceedings
    EditorsAndrea Vedaldi, Horst Bischof, Thomas Brox, Jan-Michael Frahm
    PublisherSpringer Science and Business Media Deutschland GmbH
    Pages71-89
    Number of pages19
    ISBN (Print)9783030585822
    DOIs
    Publication statusPublished - 2020
    Event16th European Conference on Computer Vision, ECCV 2020 - Glasgow, United Kingdom
    Duration: 23 Aug 202028 Aug 2020

    Publication series

    NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
    Volume12372 LNCS
    ISSN (Print)0302-9743
    ISSN (Electronic)1611-3349

    Conference

    Conference16th European Conference on Computer Vision, ECCV 2020
    Country/TerritoryUnited Kingdom
    CityGlasgow
    Period23/08/2028/08/20

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