6 papers · 1 filter
Dynamic Neural Portraits
Michail Christos Doukas, Stylianos Ploumpis, Stefanos Zafeiriou
We present Dynamic Neural Portraits, a novel approach to the problem of full-head reenactment. Our method generates photo-realistic video portraits by explicitly controlling head p…
Head2HeadFS: Video-based Head Reenactment with Few-shot Learning
Michail Christos Doukas, Mohammad Rami Koujan, Viktoriia Sharmanska +1
Over the past years, a substantial amount of work has been done on the problem of facial reenactment, with the solutions coming mainly from the graphics community. Head reenactment…
HeadGAN: One-shot Neural Head Synthesis and Editing
Michail Christos Doukas, Stefanos Zafeiriou, Viktoriia Sharmanska
Recent attempts to solve the problem of head reenactment using a single reference image have shown promising results. However, most of them either perform poorly in terms of photo-…
ReenactNet: Real-time Full Head Reenactment
Mohammad Rami Koujan, Michail Christos Doukas, Anastasios Roussos +1
Video-to-video synthesis is a challenging problem aiming at learning a translation function between a sequence of semantic maps and a photo-realistic video depicting the characteri…
Head2Head: Video-based Neural Head Synthesis
Mohammad Rami Koujan, Michail Christos Doukas, Anastasios Roussos +1
In this paper, we propose a novel machine learning architecture for facial reenactment. In particular, contrary to the model-based approaches or recent frame-based methods that use…
Video-to-Video Translation for Visual Speech Synthesis
Michail C. Doukas, Viktoriia Sharmanska, Stefanos Zafeiriou
Despite remarkable success in image-to-image translation that celebrates the advancements of generative adversarial networks (GANs), very limited attempts are known for video domai…