arxiv:2602.07106

Ex-Omni: Enabling 3D Facial Animation Generation for Omni-modal Large Language Models

Published on Feb 6

· Submitted by

Chengqian Ma on Feb 12

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Authors:

Haoyu Zhang ,

Abstract

Ex-Omni is an open-source framework that enhances omni-modal large language models with speech-accompanied 3D facial animation by decoupling semantic reasoning from temporal generation and using speech units as temporal scaffolding.

AI-generated summary

Omni-modal large language models (OLLMs) aim to unify multimodal understanding and generation, yet incorporating speech with 3D facial animation remains largely unexplored despite its importance for natural interaction. A key challenge arises from the representation mismatch between discrete, token-level semantic reasoning in LLMs and the dense, fine-grained temporal dynamics required for 3D facial motion, which makes direct modeling difficult to optimize under limited data. We propose Expressive Omni (Ex-Omni), an open-source omni-modal framework that augments OLLMs with speech-accompanied 3D facial animation. Ex-Omni reduces learning difficulty by decoupling semantic reasoning from temporal generation, leveraging speech units as temporal scaffolding and a unified token-as-query gated fusion (TQGF) mechanism for controlled semantic injection. We further introduce InstructEx, a dataset aims to facilitate augment OLLMs with speech-accompanied 3D facial animation. Extensive experiments demonstrate that Ex-Omni performs competitively against existing open-source OLLMs while enabling stable aligned speech and facial animation generation.