Title: Generating Facial Images using VAEGAN
Authors: Gruber, Ivan
Citation: RENDL, Jan ed. Studentská vědecká konference: magisterské a doktorské studijní programy, sborník rozšířených abstraktů, květen 2018, Plzeň. Plzeň: Západočeská univerzita v Plzni, 2019, s. 38-39. ISBN 978-80-261-0790-3.
Issue Date: 2018
Publisher: Západočeská univerzita v Plzni
Document type: konferenční příspěvek
URI: http://hdl.handle.net/11025/29815
ISBN: 978-80-261-0790-3
Keywords: generativní modelování;obrazy obličeje;VAEGAN
Keywords in different language: generative modelling;facial images;VAEGAN
Abstract in different language: A generative modeling is a powerful way how to learn any kind of data distribution using unsupervised learning. The main advantages of generative models are as follows: (1) they generally don’t need any labeling during training; (2) they are able to generate new data similar to existing data. Thanks to these features, generative models become very popular during last three years with a vast field of usage. In this work, I introduce an experiment of generating facial images by using VAEGAN. For the training of my model, I used CasiaWebFace database (Yi et al. (2014)) and CelebFaces Attributes dataset (Liu et al. (2015)).
Rights: © Západočeská univerzita v Plzni
Appears in Collections:Studentská vědecká konference 2018-magisterské a doktorské studijní programy
Studentská vědecká konference 2018-magisterské a doktorské studijní programy

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