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D3Net: Joint Demosaicking, Deblurring and Deringing

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    0537610 - ÚTIA 2022 RIV US eng C - Conference Paper (international conference)
    Kerepecký, Tomáš - Šroubek, Filip
    D3Net: Joint Demosaicking, Deblurring and Deringing.
    2021 25th International Conference on Pattern Recognition (ICPR). Piscataway: IEEE, 2021, s. 8283-8290. ISBN 978-172818808-9. ISSN 1051-4651.
    [2021 25th International Conference on Pattern Recognition (ICPR). Milan (IT), 10.01.2021-15.01.2021]
    R&D Projects: GA ČR GA20-27939S
    Grant - others:AV ČR(CZ) AP1701
    Program: Akademická prémie - Praemium Academiae
    Institutional support: RVO:67985556
    Keywords : demosaicking * deblurring * deringing * ADMM * CNN
    OECD category: Robotics and automatic control
    http://library.utia.cas.cz/separaty/2021/ZOI/kerepecky-0537610.pdf

    We have proposed a light-weight neural network architecture D3Net for joint demosaicking, deblurring and deringing by unrolling the ADMM optimization method.
    Permanent Link: http://hdl.handle.net/11104/0316066

     
     
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