| 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 conferenceObject |
| URI: | http://hdl.handle.net/11025/29815 http://svk.fav.zcu.cz/download/sbornik_svk_2018.pdf |
| 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 |
Files in This Item:
| File | Description | Size | Format | |
|---|---|---|---|---|
| Gruber.pdf | Plný text | 491,04 kB | Adobe PDF | View/Open |
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