Evrişimsel Aǧlar ile Sesten 3B Yüz Animasyonu Üretilmesi

Translated title of the contribution: 3D Face Animation Generation from Audio Using Convolutional Networks

Turker Unlu, Arda Inceoglu, Erkan Ozgur Yilmaz, Sanem Sariel

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

3D facial animation generation from audio problem is drawing attention as it is demanded for generating artificial characters in games and movies. In the literature, several studies address this problem. However, the generated facial animations are far away from being realistic. In this work, we represent faces with Facial Action Coding System (FACS) and collect a 37-minute-long dataset. We develop convolutional and transformer based models. It is observed that the trained model is able to generate animations that can be used in video games and virtual reality applications, even with novel speaker audio data of speakers it has never seen in the training data.

Translated title of the contribution3D Face Animation Generation from Audio Using Convolutional Networks
Original languageTurkish
Title of host publication2022 30th Signal Processing and Communications Applications Conference, SIU 2022
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781665450928
DOIs
Publication statusPublished - 2022
Event30th Signal Processing and Communications Applications Conference, SIU 2022 - Safranbolu, Turkey
Duration: 15 May 202218 May 2022

Publication series

Name2022 30th Signal Processing and Communications Applications Conference, SIU 2022

Conference

Conference30th Signal Processing and Communications Applications Conference, SIU 2022
Country/TerritoryTurkey
CitySafranbolu
Period15/05/2218/05/22

Bibliographical note

Publisher Copyright:
© 2022 IEEE.

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