Computer Science > Computer Vision and Pattern Recognition
arXiv:2407.01034 (cs)
[Submitted on 1 Jul 2024]
Title:Enhancing Speech-Driven 3D Facial Animation with Audio-Visual Guidance from Lip Reading Expert
Authors:Han EunGi,Oh Hyun-Bin,Kim Sung-Bin,Corentin Nivelet Etcheberry,Suekyeong Nam,Janghoon Joo,Tae-Hyun Oh
View a PDF of the paper titled Enhancing Speech-Driven 3D Facial Animation with Audio-Visual Guidance from Lip Reading Expert, by Han EunGi and 6 other authors
View PDFHTML (experimental)Abstract:Speech-driven 3D facial animation has recently garnered attention due to its cost-effective usability in multimedia production. However, most current advances overlook the intelligibility of lip movements, limiting the realism of facial expressions. In this paper, we introduce a method for speech-driven 3D facial animation to generate accurate lip movements, proposing an audio-visual multimodal perceptual loss. This loss provides guidance to train the speech-driven 3D facial animators to generate plausible lip motions aligned with the spoken transcripts. Furthermore, to incorporate the proposed audio-visual perceptual loss, we devise an audio-visual lip reading expert leveraging its prior knowledge about correlations between speech and lip motions. We validate the effectiveness of our approach through broad experiments, showing noticeable improvements in lip synchronization and lip readability performance. Codes are available atthis https URL.
| Comments: | INTERSPEECH 2024 |
| Subjects: | Computer Vision and Pattern Recognition (cs.CV); Graphics (cs.GR) |
| Cite as: | arXiv:2407.01034 [cs.CV] |
| (orarXiv:2407.01034v1 [cs.CV] for this version) | |
| https://doi.org/10.48550/arXiv.2407.01034 arXiv-issued DOI via DataCite |
Full-text links:
Access Paper:
- View PDF
- HTML (experimental)
- TeX Source
- Other Formats
View a PDF of the paper titled Enhancing Speech-Driven 3D Facial Animation with Audio-Visual Guidance from Lip Reading Expert, by Han EunGi and 6 other authors
References & Citations
Bookmark
Bibliographic and Citation Tools
Bibliographic Explorer(What is the Explorer?)
Connected Papers(What is Connected Papers?)
Litmaps(What is Litmaps?)
scite Smart Citations(What are Smart Citations?)
Code, Data and Media Associated with this Article
alphaXiv(What is alphaXiv?)
CatalyzeX Code Finder for Papers(What is CatalyzeX?)
DagsHub(What is DagsHub?)
Gotit.pub(What is GotitPub?)
Hugging Face(What is Huggingface?)
Papers with Code(What is Papers with Code?)
ScienceCast(What is ScienceCast?)
Demos
Recommenders and Search Tools
Influence Flower(What are Influence Flowers?)
CORE Recommender(What is CORE?)
arXivLabs: experimental projects with community collaborators
arXivLabs is a framework that allows collaborators to develop and share new arXiv features directly on our website.
Both individuals and organizations that work with arXivLabs have embraced and accepted our values of openness, community, excellence, and user data privacy. arXiv is committed to these values and only works with partners that adhere to them.
Have an idea for a project that will add value for arXiv's community?Learn more about arXivLabs.