Deep Multi Depth Panoramas for View Synthesis

Kai En Lin, Zexiang Xu, Ben Mildenhall, Pratul P. Srinivasan, Yannick Hold-Geoffroy, Stephen DiVerdi, Qi Sun, Kalyan Sunkavalli, Ravi Ramamoorthi

    Research output: Chapter in Book/Report/Conference proceedingConference contribution

    Abstract

    We propose a learning-based approach for novel view synthesis for multi-camera 360 panorama capture rigs. Previous work constructs RGBD panoramas from such data, allowing for view synthesis with small amounts of translation, but cannot handle the disocclusions and view-dependent effects that are caused by large translations. To address this issue, we present a novel scene representation—Multi Depth Panorama (MDP)—that consists of multiple RGBDα panoramas that represent both scene geometry and appearance. We demonstrate a deep neural network-based method to reconstruct MDPs from multi-camera 360 images. MDPs are more compact than previous 3D scene representations and enable high-quality, efficient new view rendering. We demonstrate this via experiments on both synthetic and real data and comparisons with previous state-of-the-art methods spanning both learning-based approaches and classical RGBD-based methods.

    Original languageEnglish (US)
    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
    Pages328-344
    Number of pages17
    ISBN (Print)9783030586003
    DOIs
    StatePublished - 2020
    Event16th European Conference on Computer Vision, ECCV 2020 - Glasgow, United Kingdom
    Duration: Aug 23 2020Aug 28 2020

    Publication series

    NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
    Volume12358 LNCS
    ISSN (Print)0302-9743
    ISSN (Electronic)1611-3349

    Conference

    Conference16th European Conference on Computer Vision, ECCV 2020
    Country/TerritoryUnited Kingdom
    CityGlasgow
    Period8/23/208/28/20

    Keywords

    • 360 panoramas
    • Image-based rendering
    • View synthesis
    • Virtual reality

    ASJC Scopus subject areas

    • Theoretical Computer Science
    • Computer Science(all)

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