Summary of Probtalk3d: Non-deterministic Emotion Controllable Speech-driven 3d Facial Animation Synthesis Using Vq-vae, by Sichun Wu and Kazi Injamamul Haque and Zerrin Yumak
ProbTalk3D: Non-Deterministic Emotion Controllable Speech-Driven 3D Facial Animation Synthesis Using VQ-VAE
by Sichun Wu, Kazi Injamamul Haque, Zerrin Yumak
First submitted to arxiv on: 12 Sep 2024
Categories
- Main: Computer Vision and Pattern Recognition (cs.CV)
- Secondary: Artificial Intelligence (cs.AI)
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| Summary difficulty | Written by | Summary |
|---|---|---|
| High | Paper authors | High Difficulty Summary Read the original abstract here |
| Medium | GrooveSquid.com (original content) | Medium Difficulty Summary The proposed ProbTalk3D neural network approach is a non-deterministic method for emotion-controllable speech-driven 3D facial animation synthesis. It uses a two-stage VQ-VAE model and an emotionally rich facial animation dataset, 3DMEAD, to generate diverse and emotionally-rich facial animations. The model’s performance is evaluated objectively using various metrics and subjectively through a perceptual user study, demonstrating superior results compared to state-of-the-art models. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary This paper creates a way for computers to make realistic 3D faces that can express different emotions when speaking. Right now, most 3D face models are good at mimicking lips moving in sync with speech, but they don’t capture the full range of emotions we use when communicating. The researchers developed a new model called ProbTalk3D that can create more expressive and emotional 3D faces by using a special type of neural network and a big dataset of facial animations. |
Keywords
» Artificial intelligence » Neural network
