Original title: Zvýšení kvality v obrazu obličeje s použitím sekvence snímků
Translated title: Increasing quality of facial images using sequence of images
Authors: Svorad, Adam ; Mezina, Anzhelika (referee) ; Burget, Radim (advisor)
Document type: Master’s theses
Year: 2021
Language: eng
Publisher: Vysoké učení technické v Brně. Fakulta elektrotechniky a komunikačních technologií
Abstract: [eng] [cze]
Diplomova praca sa zameriava na oblast zaostrovania obrazkov tvari. V teoretickej casti prace budu prezentovane moderne metody zaostrovania obrazkov pomocou jedineho obrazku a metody editacie obrazkov. Prakticka cast sa zameria na pristupy rekonstrukcie obrazkov zo sekvencie poskodenych obrazkov. Viacere modely neuronovych sieti so vstupom pre viacero obrazkov budu zhotovene a vyhodnotene. Alternativny pristup v podobe balika nastrojov na editaciu obrazkov bude taktiez predstaveny. Tieto nastroje budu vyuzivat najmodernejsie pristupy k editacii obrazkov s cielom spojit vizualne prvky tvari zo vstupnej sekvencie obrazkov do jedneho finalneho vystupu. V zavere prace budu vsetky metody navzajom porovnane. Master’s thesis delves into the field of face super-resolution. It aims to review novel approaches to single-frame image sharpening and image editing in the theoretical part of the work. Practical part will focus on approaches to image reconstruction from a sequence of damaged images. Multiple multi-frame neural network models will be implemented and evaluated. As alternative option, a suite of image editing tools will be presented as well. These tools will utilize most modern image editing techniques to merge visual features of faces from multiple input images into a single output image. At the end of the thesis, all methods will be compared to each other.
Keywords: GAN; konvolucne neuronove siete; multi-frame superrozlisenie; single-frame zaostrenie; StyleGAN; superrozlisenie tvare; U-Net; convolutional neural network; face super-resolution; GAN; multi-frame super-resolution; single- frame sharpening; StyleGAN; U-Net

Institution: Brno University of Technology (web)
Document availability information: Fulltext is available in the Brno University of Technology Digital Library.
Original record: http://hdl.handle.net/11012/196905

Permalink: http://www.nusl.cz/ntk/nusl-552143


The record appears in these collections:
Universities and colleges > Public universities > Brno University of Technology
Academic theses (ETDs) > Master’s theses