Media2Face: Co-speech Facial Animation Generation With Multi-Modality Guidance-Reference-Cited by-同舟云学术

Media2Face: Co-speech Facial Animation Generation With Multi-Modality Guidance

Published:2024-07-13 Issue: Volume: Page:1-13
ISSN:
Container-title:Special Interest Group on Computer Graphics and Interactive Techniques Conference Conference Papers '24
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Author:

Zhao Qingcheng¹^ORCID,Long Pengyu¹^ORCID,Zhang Qixuan¹^ORCID,Qin Dafei²^ORCID,Liang Han³^ORCID,Zhang Longwen¹^ORCID,Zhang Yingliang⁴^ORCID,Yu Jingyi³^ORCID,Xu Lan³^ORCID

Affiliation:

1. ShanghaiTech University, China and Deemos Technology, China

2. University of Hong Kong, China and Deemos Technology, China

3. ShanghaiTech University, China

4. DGene Digital Technology Co., Ltd., China

Funder

STCSM

National Key R&D Program of China

NSFC programs

Shanghai Frontiers Science Center of Human-centered Artificial Intelligence

SHMEC

Publisher

ACM

Reference89 articles.

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3. Tenglong Ao Zeyi Zhang and Libin Liu. 2023. GestureDiffuCLIP: Gesture Diffusion Model with CLIP Latents. ACM Trans. Graph. (2023) 18 pages. https://doi.org/10.1145/3592097

4. Alexei Baevski, Henry Zhou, Abdelrahman Mohamed, and Michael Auli. 2020. wav2vec 2.0: a framework for self-supervised learning of speech representations. In Proceedings of the 34th International Conference on Neural Information Processing Systems (Vancouver, BC, Canada) (NIPS’20). Curran Associates Inc., Red Hook, NY, USA, Article 1044, 12 pages.

5. A morphable model for the synthesis of 3D faces