no code implementations • 25 Mar 2024 • Stella Bounareli, Christos Tzelepis, Vasileios Argyriou, Ioannis Patras, Georgios Tzimiropoulos
To this end, in this paper we present DiffusionAct, a novel method that leverages the photo-realistic image generation of diffusion models to perform neural face reenactment.
no code implementations • 5 Feb 2024 • Stella Bounareli, Christos Tzelepis, Vasileios Argyriou, Ioannis Patras, Georgios Tzimiropoulos
Moreover, we show that by embedding real images in the GAN latent space, our method can be successfully used for the reenactment of real-world faces.
1 code implementation • ICCV 2023 • Stella Bounareli, Christos Tzelepis, Vasileios Argyriou, Ioannis Patras, Georgios Tzimiropoulos
In this paper, we present our method for neural face reenactment, called HyperReenact, that aims to generate realistic talking head images of a source identity, driven by a target facial pose.
1 code implementation • 27 Sep 2022 • Stella Bounareli, Christos Tzelepis, Vasileios Argyriou, Ioannis Patras, Georgios Tzimiropoulos
In this paper we address the problem of neural face reenactment, where, given a pair of a source and a target facial image, we need to transfer the target's pose (defined as the head pose and its facial expressions) to the source image, by preserving at the same time the source's identity characteristics (e. g., facial shape, hair style, etc), even in the challenging case where the source and the target faces belong to different identities.
1 code implementation • 31 Jan 2022 • Stella Bounareli, Vasileios Argyriou, Georgios Tzimiropoulos
Moreover, we show that by embedding real images in the GAN latent space, our method can be successfully used for the reenactment of real-world faces.