March 25, 2024, 4:44 a.m. | Haoxuan Qu, Ziyan Guo, Jun Liu

cs.CV updates on arXiv.org arxiv.org

arXiv:2403.14947v1 Announce Type: new
Abstract: Recently, while text-driven human motion generation has received massive research attention, most existing text-driven motion generators are generally only designed to generate motion sequences in a blank background. While this is the case, in practice, human beings naturally perform their motions in 3D scenes, rather than in a blank background. Considering this, we here aim to perform scene-aware text-drive motion generation instead. Yet, intuitively training a separate scene-aware motion generator in a supervised way can …

3d scenes abstract arxiv attention beings case cs.cv free generate generator generators gpt human massive practice research text training type

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