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    Day-to-Night Road Scene Image Translation Using Semantic Segmentation

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    Date
    2020
    Author
    Baek, Seung Youp
    Lee, Sungkil
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    Abstract
    We present a semi-automated framework that translates day-time domain road scene images to those for the night-time domain. Unlike recent studies based on the Generative Adversarial Networks (GANs), we avoid learning for the translation without random failures. Our framework uses semantic annotation to extract scene elements, perceives a scene structure/depth, and applies per-element translation. Experimental results demonstrate that our framework can synthesize higher-resolution results without artifacts in the translation.
    BibTeX
    @inproceedings {.20201231,
    booktitle = {Pacific Graphics Short Papers, Posters, and Work-in-Progress Papers},
    editor = {Lee, Sung-hee and Zollmann, Stefanie and Okabe, Makoto and Wuensche, Burkhard},
    title = {{Day-to-Night Road Scene Image Translation Using Semantic Segmentation}},
    author = {Baek, Seung Youp and Lee, Sungkil},
    year = {2020},
    publisher = {The Eurographics Association},
    ISBN = {978-3-03868-120-5},
    DOI = {10.2312/pg.20201231}
    }
    URI
    https://doi.org/10.2312/pg.20201231
    https://diglib.eg.org:443/handle/10.2312/pg20201231
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    Eurographics Association copyright © 2013 - 2020 
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    Theme by @mire NV
    System hosted at  Graz University of Technology.
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