Egocentric human demonstrations offer an accessible source of task experience, but differences in body scale and controller response, together with missing robot states, limit their value as humanoid training supervision. We present EgoAlign, a data-construction framework that converts these demonstrations into action...
Yi-Ming Jiang, Jin Chen, Chong-Yang Xu et al.· 0 citations
Generating motion sequences conforming to a target style while adhering to the given content prompts requires accommodating both the content and style. In existing methods, the information usually only flows from style to content, which may cause conflict between the style and content, harming the integration. Differen...
Zhe Li, Yi-Sheng He, Lei Zhong et al.· IEEE Transactions on Image P...· 19 citations· ⚡2
This work builds a bidirectional control flow between the style and the content, also adjusting the style towards the content, in which case the style-content collision is alleviated and the dynamics of the style is better preserved in the integration.
Zhe Li, Yisheng He, Lei Zhong et al.· arXiv.org· 0 citations
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