TY - CHAP U1 - Konferenzveröffentlichung A1 - Laube, Pascal A1 - Franz, Matthias O. A1 - Grunwald, Michael A1 - Umlauf, Georg T1 - Image Inpainting for High-Resolution Textures using CNN Texture Synthesis BT - Short Paper T2 - Computer Graphics & Visual Computing (CGVC) 2018, 13th - 14th September 2018, Swansea University, United Kingdom N2 - 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) for image inpainting of large regions in high-resolution textures. Due to limited computational resources processing high-resolution images with neural networks is still an open problem. Existing methods separate inpainting of global structure and the transfer of details, which leads to blurry results and loss of global coherence in the detail transfer step. Based on advances in texture synthesis using CNNs we propose patch-based image inpainting by a single network topology that is able to optimize for global as well as detail texture statistics. Our method is capable of filling large inpainting regions, oftentimes exceeding quality of comparable methods for images of high-resolution (2048x2048px). For reference patch look-up we propose to use the same summary statistics that are used in the inpainting process. Y1 - 2018 UR - https://arxiv.org/abs/1712.03111v2 SP - 5 S1 - 5 ET - Version 2 ER -