SentiAvatar generates expressive interactive 3D avatars in real time by combining a 37-hour mocap dialogue dataset with a pre-trained motion foundation model and an audio-aware plan-then-infill architecture that separates semantic planning from prosody-driven frame interpolation.
Personabooth: Personalized text-to-motion generation
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OMG is a diffusion model for omni-modal whole-body humanoid motion generation that uses language, audio, and reference motions after large-scale data curation to achieve state-of-the-art performance and adaptation.
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SentiAvatar: Towards Expressive and Interactive Digital Humans
SentiAvatar generates expressive interactive 3D avatars in real time by combining a 37-hour mocap dialogue dataset with a pre-trained motion foundation model and an audio-aware plan-then-infill architecture that separates semantic planning from prosody-driven frame interpolation.
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OMG: Omni-Modal Motion Generation for Generalist Humanoid Control
OMG is a diffusion model for omni-modal whole-body humanoid motion generation that uses language, audio, and reference motions after large-scale data curation to achieve state-of-the-art performance and adaptation.