Emotional Talking Faces: Making Videos More Expressive and Realistic

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Emotional Talking Faces: Making Videos More Expressive and Realistic
Title:
Emotional Talking Faces: Making Videos More Expressive and Realistic
Journal Title:
Proceedings of the 4th ACM International Conference on Multimedia in Asia
Keywords:
Publication Date:
07 December 2022
Citation:
Goyal, S., Uppal, S., Bhagat, S., Goel, D., Mali, S., Yu, Y., Yin, Y., Shah, R. R. (2022). Emotional Talking Faces. Proceedings of the 4th ACM International Conference on Multimedia in Asia. https://doi.org/10.1145/3551626.3564976
Abstract:
Lip synchronization and talking face generation have gained a specific interest from the research community with the advent and need of digital communication in different fields. Prior works propose several elegant solutions to this problem. However, they often fail to create realistic-looking videos that account for people’s expressions and emotions. To mitigate this, we build a talking face generation framework conditioned on a categorical emotion to generate videos with appropriate expressions, making them more real-looking and convincing. With a broad range of six emotions i.e., anger, disgust, fear, happiness, neutral, and sad, we show that our model generalizes across identities, emotions, and languages.
License type:
Publisher Copyright
Funding Info:
Rajiv Ratn Shah is partly supported by the Infosys Center for AI and the Center of Design and New Media at IIIT Delhi.
Description:
© Author | ACM 2022. This is the author's version of the work. It is posted here for your personal use. Not for redistribution. The definitive Version of Record was published in Proceedings of the 4th ACM International Conference on Multimedia in Asia, https://doi.org/10.1145/3551626.3564976
ISBN:
978-1-4503-9478-9/22/12
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