TDMM-LM: Bridging Facial Understanding and Animation via Language Models
#TDMM-LM #language models #facial animation #AI synthesis #natural language processing
📌 Key Takeaways
- TDMM-LM integrates language models with facial analysis and animation.
- The model enhances facial understanding by leveraging natural language processing.
- It enables more intuitive animation generation from textual descriptions.
- The approach bridges gaps between facial motion capture and AI-driven synthesis.
📖 Full Retelling
arXiv:2603.16936v1 Announce Type: cross
Abstract: Text-guided human body animation has advanced rapidly, yet facial animation lags due to the scarcity of well-annotated, text-paired facial corpora. To close this gap, we leverage foundation generative models to synthesize a large, balanced corpus of facial behavior. We design prompts suite covering emotions and head motions, generate about 80 hours of facial videos with multiple generators, and fit per-frame 3D facial parameters, yielding large-
🏷️ Themes
AI Animation, Facial Analysis
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Original Source
arXiv:2603.16936v1 Announce Type: cross
Abstract: Text-guided human body animation has advanced rapidly, yet facial animation lags due to the scarcity of well-annotated, text-paired facial corpora. To close this gap, we leverage foundation generative models to synthesize a large, balanced corpus of facial behavior. We design prompts suite covering emotions and head motions, generate about 80 hours of facial videos with multiple generators, and fit per-frame 3D facial parameters, yielding large-
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