Head2Head: Video-based Neural Head Synthesis

• URL: http://arxiv.org/abs/2005.10954v1
• Date: Fri, 22 May 2020 00:44:43 GMT
• Title: Head2Head: Video-based Neural Head Synthesis
• Authors: Mohammad Rami Koujan, Michail Christos Doukas, Anastasios Roussos, Stefanos Zafeiriou
• Abstract summary: We propose a novel machine learning architecture for facial reenactment. We show that the proposed method can transfer facial expressions, pose and gaze of a source actor to a target video in a photo-realistic fashion more accurately than state-of-the-art methods.
• Score: 50.32988828989691
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: 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 Deep Convolutional Neural Networks (DCNNs) to generate individual frames, we propose a novel method that (a) exploits the special structure of facial motion (paying particular attention to mouth motion) and (b) enforces temporal consistency. We demonstrate that the proposed method can transfer facial expressions, pose and gaze of a source actor to a target video in a photo-realistic fashion more accurately than state-of-the-art methods.

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