Co-Speech Gesture and Facial Expression Generation for Non-Photorealistic 3D Characters
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Abstract (arXiv)
With the advancement of conversational AI, research on bodily expressions, including gestures and facial expressions, has also progressed. However, many existing studies focus on photorealistic avatars, making them unsuitable for non-photorealistic characters, such as those found in anime. This study proposes methods for expressing emotions, including exaggerated expressions unique to non-photorealistic characters, by utilizing expression data extracted from comics and dialogue-specific semantic gestures. A user study demonstrated significant improvements across multiple aspects when compared to existing research.
Key facts. Cited by 1 paper in the map (data through 14 Oct 2026). Builds on 3 of its 4 references that are in the map. First posted on arXiv 19 Jun 2025.
Builds on
3 of 4 references.
References · 3
- 2022BEAT: A Large-Scale Semantic and Emotional Multi-Modal Dataset for Conversational Gestures Synthesiscited by 178
- 2023EMAGE: Towards Unified Holistic Co-Speech Gesture Generation via Expressive Masked Audio Gesture Modelingcited by 105
- 2020Building a Manga Dataset "Manga109" with Annotations for Multimedia Applicationscited by 38
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Citing papers per year: 2026: 1.
1 paper.