Audio-visual Neural Face Generation with Emotional Stimuli
- Authors
- Hwang, Juheon; Kang, Jiwoo
- Issue Date
- Dec-2023
- Publisher
- Institute of Electrical and Electronics Engineers Inc.
- Keywords
- dynamic scenes; face reconstruction; Multimodal stimuli; neural rendering; novel view synthesis
- Citation
- Proceedings - 2023 IEEE International Conference on Big Data, BigData 2023, pp 2183 - 2187
- Pages
- 5
- Journal Title
- Proceedings - 2023 IEEE International Conference on Big Data, BigData 2023
- Start Page
- 2183
- End Page
- 2187
- URI
- https://scholarworks.sookmyung.ac.kr/handle/2020.sw.sookmyung/159826
- DOI
- 10.1109/BigData59044.2023.10386942
- ISSN
- 0000-0000
- Abstract
- In communication, it is important to generate realistic 3D facial avatars that can express various expressions. However, existing models have limitations in that they cannot show facial expressions in sufficient detail. To this end, we propose an audio-visual volumetric avatar generation method that reconstructs detailed facial expressions using two emotional stimuli. Emotional features extracted from the input and the rendered image induce the model to generate an avatar with the same emotion. At the same time, a speech clip is used as input along with the images, helping the model recognize the emotion of the target that is difficult to understand with the images. We showed qualitatively and qualitatively that our method achieved significantly more realistic and higher-quality avatar generation than current state-of-the-art methods. © 2023 IEEE.
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