Speech-Driven Facial Reenactment Using Conditional Generative Adversarial Networks

Autor:	Jalalifar, Seyed Ali, Hasani, Hosein, Aghajan, Hamid
Rok vydání:	2018
Předmět:	Computer Science - Computer Vision and Pattern Recognition
Druh dokumentu:	Working Paper
Popis:	We present a novel approach to generating photo-realistic images of a face with accurate lip sync, given an audio input. By using a recurrent neural network, we achieved mouth landmarks based on audio features. We exploited the power of conditional generative adversarial networks to produce highly-realistic face conditioned on a set of landmarks. These two networks together are capable of producing a sequence of natural faces in sync with an input audio track. Comment: Submitted for ECCV 2018
Databáze:	arXiv
Externí odkaz:	http://arxiv.org/abs/1803.07461 Zobrazit plný text záznamu View this record from Arxiv