SPACEx: Speech-driven Portrait Animation with Controllable Expression

• URL: http://arxiv.org/abs/2211.09809v1
• Date: Thu, 17 Nov 2022 18:59:56 GMT
• Title: SPACEx: Speech-driven Portrait Animation with Controllable Expression
• Authors: Siddharth Gururani, Arun Mallya, Ting-Chun Wang, Rafael Valle, Ming-Yu Liu
• Abstract summary: We present SPACEx, which uses speech and a single image to generate expressive videos with realistic head pose. It uses a multi-stage approach, combining the controllability of facial landmarks with the high-quality synthesis power of a pretrained face generator.
• Score: 31.99644011371433
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: Animating portraits using speech has received growing attention in recent years, with various creative and practical use cases. An ideal generated video should have good lip sync with the audio, natural facial expressions and head motions, and high frame quality. In this work, we present SPACEx, which uses speech and a single image to generate high-resolution, and expressive videos with realistic head pose, without requiring a driving video. It uses a multi-stage approach, combining the controllability of facial landmarks with the high-quality synthesis power of a pretrained face generator. SPACEx also allows for the control of emotions and their intensities. Our method outperforms prior methods in objective metrics for image quality and facial motions and is strongly preferred by users in pair-wise comparisons. The project website is available at https://deepimagination.cc/SPACEx/

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