Talking-head Generation with Rhythmic Head Motion
July 16, 2020 ยท Declared Dead ยท ๐ European Conference on Computer Vision
"No code URL or promise found in abstract"
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Authors
Lele Chen, Guofeng Cui, Celong Liu, Zhong Li, Ziyi Kou, Yi Xu, Chenliang Xu
arXiv ID
2007.08547
Category
cs.CV: Computer Vision
Cross-listed
cs.GR
Citations
201
Venue
European Conference on Computer Vision
Last Checked
2 months ago
Abstract
When people deliver a speech, they naturally move heads, and this rhythmic head motion conveys prosodic information. However, generating a lip-synced video while moving head naturally is challenging. While remarkably successful, existing works either generate still talkingface videos or rely on landmark/video frames as sparse/dense mapping guidance to generate head movements, which leads to unrealistic or uncontrollable video synthesis. To overcome the limitations, we propose a 3D-aware generative network along with a hybrid embedding module and a non-linear composition module. Through modeling the head motion and facial expressions1 explicitly, manipulating 3D animation carefully, and embedding reference images dynamically, our approach achieves controllable, photo-realistic, and temporally coherent talking-head videos with natural head movements. Thoughtful experiments on several standard benchmarks demonstrate that our method achieves significantly better results than the state-of-the-art methods in both quantitative and qualitative comparisons. The code is available on https://github.com/ lelechen63/Talking-head-Generation-with-Rhythmic-Head-Motion.
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