EMAGE: Towards Unified Holistic Co-Speech Gesture Generation via Expressive Masked Audio Gesture Modeling
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Abstract (arXiv)
We propose EMAGE, a framework to generate full-body human gestures from audio and masked gestures, encompassing facial, local body, hands, and global movements. To achieve this, we first introduce BEAT2 (BEAT-SMPLX-FLAME), a new mesh-level holistic co-speech dataset. BEAT2 combines a MoShed SMPL-X body with FLAME head parameters and further refines the modeling of head, neck, and finger movements, offering a community-standardized, high-quality 3D motion captured dataset. EMAGE leverages masked body gesture priors during training to boost inference performance. It involves a Masked Audio Gesture Transformer, facilitating joint training on audio-to-gesture generation and masked gesture reconstruction to effectively encode audio and body gesture hints. Encoded body hints from masked gestures are then separately employed to generate facial and body movements. Moreover, EMAGE adaptively merges speech features from the audio's rhythm and content and utilizes four compositional VQ-VAEs to enhance the results' fidelity and diversity. Experiments demonstrate that EMAGE generates holistic gestures with state-of-the-art performance and is flexible in accepting predefined spatial-temporal gesture inputs, generating complete, audio-synchronized results. Our code and dataset are available https://pantomatrix.github.io/EMAGE/
Key facts. Cited by 101 papers in the map (data through 7 Oct 2026). Builds on 58 of its 81 references that are in the map. First posted on arXiv 31 Dec 2023.
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58 of 81 references.
References · 58
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- 2020Skeleton-Aware Networks for Deep Motion Retargetingcited by 118
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- 2021Learning Speech-driven 3D Conversational Gestures from Videocited by 98
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- 2020Style Transfer for Co-Speech Gesture Animation: A Multi-Speaker Conditional-Mixture Approachcited by 64
- 2021Speech Drives Templates: Co-Speech Gesture Synthesis with Learned Templatescited by 57
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- 2023EmotionGesture: Audio-Driven Diverse Emotional Co-Speech 3D Gesture Generationcited by 40
- 2023LivelySpeaker: Towards Semantic-Aware Co-Speech Gesture Generationcited by 40
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- 2022Differentiable Dynamics for Articulated 3d Human Motion Reconstructioncited by 38
- 2020Body2Hands: Learning to Infer 3D Hands from Conversational Gesture Body Dynamicscited by 34
50 most cited of 58 All 58 (JSON)
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Citing papers per year: 2024: 12; 2025: 41; 2026: 48.
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