Deep Terrain Expansion: Terrain Texture Synthesis with Deep Learning

Toulatzis, Vasilis; Fudos, Ioannis

Deep Terrain Expansion: Terrain Texture Synthesis with Deep Learning

Files

095-096.pdf (5.21 MB)

paper1014-supplementary-material.pdf (938.04 KB)

Date

2019

Authors

Toulatzis, Vasilis
Fudos, Ioannis

Publisher

The Eurographics Association

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.

        @inproceedings{10.2312:cgvc.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
}
}