PhysDrift: Bridging the Embodiment Gap in Humanoid Co-Speech Motion Generation
Humanoid robots require co-speech motions that are not only expressive and speech-aligned, but also physically executable under embodiment constraints. Existing co-speech generation pipelines are predominantly human-centric: motions are first generated in human-body representations such as SMPL-X and subsequently retargeted to humanoid robots. In this work, we identify a fundamental embodiment gap in this paradigm, where the mismatch between human motion manifolds and humanoid embodiment constraints disrupts embodiment consistency during motion transfer and physical execution. Through extensive analysis, we show that although retargeting can preserve coarse motion semantics, it significan...
| Authors | Zhangzhao Liang, Xiaofen Xing, Mingyue Yang et al. |
|---|---|
| Primary category | cs.AI |
| Published | 18 June 2026 |
| Last updated at source | 18 June 2026 |
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