Deep Texture and Structure Aware Filtering Network for Image Smoothing

Kaiyue Lu*, Shaodi You, Nick Barnes

*Corresponding author for this work

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

    9 Citations (Scopus)

    Abstract

    Image smoothing is a fundamental task in computer vision, that attempts to retain salient structures and remove insignificant textures. In this paper, we aim to address the fundamental shortcomings of existing image smoothing methods, which cannot properly distinguish textures and structures with similar low-level appearance. While deep learning approaches have started to explore structure preservation through image smoothing, existing work does not yet properly address textures. To this end, we generate a large dataset by blending natural textures with clean structure-only images, and use this to build a texture prediction network (TPN) that predicts the location and magnitude of textures. We then combine the TPN with a semantic structure prediction network (SPN) so that the final texture and structure aware filtering network (TSAFN) is able to identify the textures to remove (“texture-awareness”) and the structures to preserve (“structure-awareness”). The proposed model is easy to understand and implement, and shows good performance on real images in the wild as well as our generated dataset.

    Original languageEnglish
    Title of host publicationComputer Vision – ECCV 2018 - 15th European Conference, 2018, Proceedings
    EditorsVittorio Ferrari, Cristian Sminchisescu, Yair Weiss, Martial Hebert
    PublisherSpringer Verlag
    Pages229-245
    Number of pages17
    ISBN (Print)9783030012243
    DOIs
    Publication statusPublished - 2018
    Event15th European Conference on Computer Vision, ECCV 2018 - Munich, Germany
    Duration: 8 Sept 201814 Sept 2018

    Publication series

    NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
    Volume11208 LNCS
    ISSN (Print)0302-9743
    ISSN (Electronic)1611-3349

    Conference

    Conference15th European Conference on Computer Vision, ECCV 2018
    Country/TerritoryGermany
    CityMunich
    Period8/09/1814/09/18

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