activity
20192022
most citedHead2Head++: Deep Facial Attributes Re-Targeting

49 citations · 54 across the 6 of their papers we have counts for

collaborators

9 papers

cs.CV2022★ 2 cited

3DGazeNet: Generalizing Gaze Estimation with Weak-Supervision from Synthetic Views

Evangelos Ververas, Polydefkis Gkagkos, Jiankang Deng +3

Developing gaze estimation models that generalize well to unseen domains and in-the-wild conditions remains a challenge with no known best solution. This is mostly due to the diffi…

cs.CV2022

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…

cs.CV2022★ 3 cited

Free-HeadGAN: Neural Talking Head Synthesis with Explicit Gaze Control

Michail Christos Doukas, Evangelos Ververas, Viktoriia Sharmanska +1

We present Free-HeadGAN, a person-generic neural talking head synthesis system. We show that modeling faces with sparse 3D facial landmarks are sufficient for achieving state-of-th…

cs.CV2021

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…

cs.CV2020

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-…

cs.CV2020★ 49 cited

Head2Head++: Deep Facial Attributes Re-Targeting

Michail Christos Doukas, Mohammad Rami Koujan, Viktoriia Sharmanska +1

Facial video re-targeting is a challenging problem aiming to modify the facial attributes of a target subject in a seamless manner by a driving monocular sequence. We leverage the…