Face-reenactment: generation flexibility  and identity preservation

dc.contributor.author	Petruk, Marian
dc.date.accessioned	2024-02-15T08:26:49Z
dc.date.available	2024-02-15T08:26:49Z
dc.date.issued	2020
dc.identifier.citation	Petruk, Marian. Face-reenactment: generation flexibility and identity preservation / Petruk, Marian; Supervisor: Markian Kostiv; Ukrainian Catholic University, Department of Computer Sciences. – Lviv: 2020. – 44 p.	uk
dc.identifier.uri	https://er.ucu.edu.ua/handle/1/4494
dc.language.iso	en	uk
dc.title	Face-reenactment: generation flexibility and identity preservation	uk
dc.type	Preprint	uk
dc.status	Публікується вперше	uk
dc.description.abstracten	Face-reenactment, also knows as puppetry, has become very popular in recent years. The proposed task requires generating new face expression while preserv- ing person identity and scene features. In this work, we propose advancements for recent novel methods of accurate face-reenactment synthesis. We present results us- ing a flexible generation module, and compare different families of encoding back- bones, introduce identity loss to preserve a person’s identity in image generation with state-of-the-art models in the deep face-recognition domain. We also provide improvements in the training procedure and test on approach weaknesses.	uk