Now showing items 1-4 of 4

    • A Deep Learning Approach to No-Reference Image Quality Assessment For Monte Carlo Rendered Images 

      Whittle, Joss; Jones, Mark W. (The Eurographics Association, 2018)
      In Full-Reference Image Quality Assessment (FR-IQA) images are compared with ground truth images that are known to be of high visual quality. These metrics are utilized in order to rank algorithms under test on their image ...
    • Groupwise Non-rigid Image Alignment With Graph-based Initialisation 

      Aal-Yhia, Ahmad; Malcolm, Paul; Akanyeti, Otar; Zwiggelaar, Reyer; Tiddeman, Bernard (The Eurographics Association, 2018)
      Groupwise image alignment automatically provides non-rigid registration across a set of images. It has found applications in facial image analysis and medical image analysis by automatically generating statistical models ...
    • Image Inpainting for High-Resolution Textures using CNN Texture Synthesis 

      Laube, Pascal; Grunwald, Michael; Franz, Matthias O.; Umlauf, Georg (The Eurographics Association, 2018)
      Deep neural networks have been successfully applied to problems such as image segmentation, image super-resolution, coloration and image inpainting. In this work we propose the use of convolutional neural networks (CNN) ...
    • Segmenting Teeth from Volumetric CT Data with a Hierarchical CNN-based Approach 

      Macho, Philipp Marten; Kurz, Nadja; Ulges, Adrian; Brylka, Robert; Gietzen, Thomas; Schwanecke, Ulrich (The Eurographics Association, 2018)
      This paper addresses the automatic segmentation of teeth in volumetric Computed Tomography (CT) scans of the human skull. Our approach is based on a convolutional neural network employing 3D volumetric convolutions. To ...