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    Deep Terrain Expansion: Terrain Texture Synthesis with Deep Learning

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    Date
    2019
    Author
    Toulatzis, Vasilis
    Fudos, Ioannis
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    Abstract
    In real-world applications terrains play a cardinal role in the field of games and geospatial applications such as Geographic Information Systems (GIS). The textures of a terrain are essential for creating virtual photorealistic environments for users. In many cases, the entire texture of a region is not available in high resolution or is much smaller than the required texture to cover a terrain. Tiling of a texture across a terrain or using an enlarged version of it usually fails to provide an acceptable photorealistic result. Consequently, high quality texture synthesis is a central issue in such settings. In this paper, we explore a novel methodology that extends previous work providing both synthesis and expansion/shrinkage of a texture.
    BibTeX
    @inproceedings {vc.20191262,
    booktitle = {Computer Graphics and Visual Computing (CGVC)},
    editor = {Vidal, Franck P. and Tam, Gary K. L. and Roberts, Jonathan C.},
    title = {{Deep Terrain Expansion: Terrain Texture Synthesis with Deep Learning}},
    author = {Toulatzis, Vasilis and Fudos, Ioannis},
    year = {2019},
    publisher = {The Eurographics Association},
    ISBN = {978-3-03868-096-3},
    DOI = {10.2312/cgvc.20191262}
    }
    URI
    https://doi.org/10.2312/cgvc.20191262
    https://diglib.eg.org:443/handle/10.2312/cgvc20191262
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    • Computer Graphics & Visual Computing (CGVC) 2019

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