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Staranje obrazov s pomočjo globokih generativnih nevronskih mrež : magistrsko delo
ID Vesel, Nejc (Author), ID Peer, Peter (Mentor) More about this mentor... This link opens in a new window, ID Meden, Blaž (Co-mentor), ID Štruc, Vitomir (Co-mentor)

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Abstract
Staranje obrazov je področje, ki se ukvarja z modeliranjem staranja osebe iz ene same referenčne slike. Želimo ustvariti generativni model, ki nam s pomočjo nevronskih mrež ustvari slike referenčne osebe pri različnih starostnih skupinah. Pri našem pristopu smo želeli cilj doseči z uporabo različnih generativnih arhitektur. Preizkusili smo nekaj uveljavljenih pristopov ter implementirali nekaj lastnih idej, ki se niso izkazale za najuspešnejše. Dobljeni končni rezultati so bili pod pričakovanji, vendar naloga naredi pregled nad preizkušenimi pristopi in njihovo implementacijo. Naloga predstavlja dobro podlago za nadaljnje raziskovanje na tem področju, saj naredi pregled nad uspešnimi in neuspešnimi pristopi ter težavami, ki se pojavljajo pri raziskovanju tega področja.

Language:Slovenian
Keywords:staranje obrazov, variacijski avtoenkoder, generativne mreže, nevronske mreže, generativne nasprotniške mreže, nasprotniški avtoenkoder
Work type:Master's thesis/paper (mb22)
Typology:2.09 - Master's Thesis
Organization:FMF - Faculty of Mathematics and Physics
Year:2019
UDC:004
COBISS.SI-ID:18607449 This link opens in a new window
Publication date in RUL:28.01.2019
Views:895
Downloads:474
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Secondary language

Language:English
Title:Face aging using deep generative neural networks
Abstract:
Face aging as a research topic is dealing with modelling human aging from a reference photo. We want a generative model that, using generative neural networks, generates images of a reference person at a different age. We implemented some existing approaches and developed some of our own, however, they didn't return results that we wished for. The final results were below expectations, however, the thesis makes a good overview over the implemented approaches and their implementation. The thesis creates a good foundation for further research. It gives a good overview over successful and non successful approaches and the difficulties that arise when doing research on this topic.

Keywords:face aging, variational autoencoder, generative networks, neural networks, generative adverserial networks, adverserial autoencoders

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