English(EN) STyMo: Fast and Controllable Few-Shot Motion Style Transfer

STyMo 实现快速、可控的少样本运动风格迁移

作者 PulseAugur 编辑部 · [1 个来源] · 2026-09-07 04:00

研究人员开发了 STyMo，一种新颖的少样本运动风格迁移方法，仅需几秒钟的配对数据即可在几分钟内完成训练。该方法将运动风格分解为静态和时间分量，允许在运行时调整姿势强度、时间夸张和区域风格。STyMo 还包含一个风格化门控，以防止对分布外运动产生伪影，并发布了一个处理后的数据集以鼓励进一步研究。 AI

影响能够更高效、更灵活地创建多样化的虚拟角色动画。

排序理由该条目描述了一篇详细介绍新颖运动风格迁移方法的最新研究论文。[lever_c_demoted from research: ic=1 ai=0.7]

在 arXiv cs.CV 阅读 →

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报道来源 [1]

arXiv cs.CV TIER_1 English(EN) · Jose Luis Ponton, Alexander Winkler, Ladislav Kavan, Yuting Ye, Petr Kadlecek · 2026-09-07 04:00

STyMo：快速可控的少样本运动风格迁移

arXiv:2609.04500v1 Announce Type: cross Abstract: Supporting a wide variety of motion styles is critical for creating diverse virtual characters, but current methods either require large stylized datasets or pre-trained models that cannot generalize beyond their training distribu…

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STyMo：快速可控的少样本运动风格迁移

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