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master's thesis
Frontalizacija lica temeljena na dubokim generativnim modelima
Zagreb: University of Zagreb, Faculty of Electrical Engineering and Computing, 2022. urn:nbn:hr:168:880501
Mesec, Patrik
University of Zagreb
Faculty of Electrical Engineering and Computing

Institutional repository: FER Repository

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Mesec, P. (2022). Frontalizacija lica temeljena na dubokim generativnim modelima (Master's thesis). Zagreb: University of Zagreb, Faculty of Electrical Engineering and Computing. Retrieved from https://urn.nsk.hr/urn:nbn:hr:168:880501

Mesec, Patrik. "Frontalizacija lica temeljena na dubokim generativnim modelima." Master's thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, 2022. https://urn.nsk.hr/urn:nbn:hr:168:880501

Mesec, Patrik. "Frontalizacija lica temeljena na dubokim generativnim modelima." Master's thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, 2022. https://urn.nsk.hr/urn:nbn:hr:168:880501

Mesec, P. (2022). 'Frontalizacija lica temeljena na dubokim generativnim modelima', Master's thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, accessed 27 December 2024, https://urn.nsk.hr/urn:nbn:hr:168:880501

Mesec P. Frontalizacija lica temeljena na dubokim generativnim modelima [Master's thesis]. Zagreb: University of Zagreb, Faculty of Electrical Engineering and Computing; 2022 [cited 2024 December 27] Available at: https://urn.nsk.hr/urn:nbn:hr:168:880501

P. Mesec, "Frontalizacija lica temeljena na dubokim generativnim modelima", Master's thesis, University of Zagreb, Faculty of Electrical Engineering and Computing, Zagreb, 2022. Available at: https://urn.nsk.hr/urn:nbn:hr:168:880501

Metadata
TitleFrontalizacija lica temeljena na dubokim generativnim modelima
Title (english)Face Frontalization Using Deep Generative Models
AuthorPatrik Mesec
MentorAlan Jović (mentor)
Committee memberAlan Jović (predsjednik povjerenstva)
Committee memberAnte Đerek (član povjerenstva)
Committee memberMarin Golub (član povjerenstva)
GranterUniversity of Zagreb
Faculty of Electrical Engineering and Computing
Zagreb
Defense date and country2022-07-06, Croatia
Scientific / art field,
discipline and subdiscipline		TECHNICAL SCIENCES
Computing
Abstract
Suvremeni modeli identifikacije lica imaju manju točnost na profilnim pozama lica, posebice u ekstremnim slučajevima. Glavni cilj rada bio je izrada modela za ostvarivanje prednjeg pogleda na lice (frontalizacija) s ciljem poboljšanja točnosti identifikacije lica. Najvažniji dio rada bio je sakupljanje kritične količine podataka pomoću kojih je učeno nekoliko dubokih generativnih modela. Najbolji naučeni model temelji se na arhitekturi modela FFWM. Učene su različite varijacije modela FFWM, te je prikazan utjecaj pojedinih komponenti modela. Točnost identifikacije lica mjerena je na više različitih modela za izlučivanje značajki lica na skupu za evaluaciju. Frontalizacijom lica ostvarena su značajna poboljšanja identifikacije lica na svim modelima. Osim kvantitativne evaluacije, dana je i vizualizacija ostvarenih rezultata frontalizacije na skupu za evaluaciju i na dodatnim primjercima iz različitih izvora.
Abstract (english)
Modern face identification models have worse accuracy on the profile poses of the face, especially in extreme cases. The main goal of this thesis was to develop a model for the face frontalization with the aim of improving the accuracy of face identification. The most important part of the work was the collection of a critical amount of data by which several deep generative models were trained. The best trained model is based on the architecture of the FFWM model. Different variations of the FFWM model were trained and the influence of some model components was shown. The accuracy of face identification was measured on several different models for extracting facial features on validation set. Face frontalization led to a significant improvement of face identification on all models. In addition to quantitative evaluation, the face frontalization results achieved on the validation set and additional examples from various sources were also visualized.
Keywords
Keywords (english)
Languagecroatian
URN:NBNurn:nbn:hr:168:880501
Study programmeTitle: Computing
Study programme type: university
Study level: graduate
Academic / professional title: magistar/magistra inženjer/inženjerka računarstva (magistar/magistra inženjer/inženjerka računarstva)
Type of resourceText
File originBorn digital
Access conditionsClosed access
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Created on2023-01-14 09:32:06