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FG-MDM: Towards Zero-Shot Human Motion Generation via Fine-Grained Descriptions
April 24, 2024, 4:45 a.m. | Xu Shi, Wei Yao, Chuanchen Luo, Junran Peng, Hongwen Zhang, Yunlian Sun
cs.CV updates on arXiv.org arxiv.org
Abstract: Recently, significant progress has been made in text-based motion generation, enabling the generation of diverse and high-quality human motions that conform to textual descriptions. However, generating motions beyond the distribution of original datasets remains challenging, i.e., zero-shot generation. By adopting a divide-and-conquer strategy, we propose a new framework named Fine-Grained Human Motion Diffusion Model (FG-MDM) for zero-shot human motion generation. Specifically, we first parse previous vague textual annotations into fine-grained descriptions of different body parts …
abstract arxiv beyond cs.cv datasets distribution diverse enabling fine-grained however human mdm progress quality strategy text textual type via zero-shot
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