Deep Terrain Expansion: Terrain Texture Synthesis with Deep Learning
| dc.contributor.author | Toulatzis, Vasilis | en_US |
| dc.contributor.author | Fudos, Ioannis | en_US |
| dc.contributor.editor | Vidal, Franck P. and Tam, Gary K. L. and Roberts, Jonathan C. | en_US |
| dc.date.accessioned | 2019-09-11T05:09:05Z | |
| dc.date.available | 2019-09-11T05:09:05Z | |
| dc.date.issued | 2019 | |
| dc.description.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. | en_US |
| dc.description.sectionheaders | Posters | |
| dc.description.seriesinformation | Computer Graphics and Visual Computing (CGVC) | |
| dc.identifier.doi | 10.2312/cgvc.20191262 | |
| dc.identifier.isbn | 978-3-03868-096-3 | |
| dc.identifier.pages | 95-96 | |
| dc.identifier.uri | https://doi.org/10.2312/cgvc.20191262 | |
| dc.identifier.uri | https://diglib.eg.org:443/handle/10.2312/cgvc20191262 | |
| dc.publisher | The Eurographics Association | en_US |
| dc.title | Deep Terrain Expansion: Terrain Texture Synthesis with Deep Learning | en_US |