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English(EN) Wave2Body: Rethinking mmWave Human Pose Estimation as Radar-to-Body Token Translation

Wave2Body框架使用雷达将信号转换为人体姿态估计

研究人员推出了一种新颖的利用毫米波(mmWave)雷达进行人体姿态估计的框架Wave2Body。与直接回归关节坐标的先前方法不同,Wave2Body通过采用自监督毫米波标记器、预训练的组合身体标记器和轻量级翻译器来解耦学习目标。该方法旨在提高跨域泛化能力并降低计算成本。在M4Human和mmBody数据集上的实验证明了Wave2Body的有效性。 AI

影响 该框架有望实现更具隐私友好性和计算效率的人体感知应用。

排序理由 该集群包含一篇详细介绍新的人体姿态估计框架的研究论文。[lever_c_demoted from research: ic=1 ai=1.0]

在 arXiv cs.CV 阅读 →

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Wave2Body框架使用雷达将信号转换为人体姿态估计

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该集群包含一篇详细介绍新的人体姿态估计框架的研究论文。[lever_c_demoted from research: ic=1 ai=1.0]
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报道来源 [1]

  1. arXiv cs.CV TIER_1 English(EN) · Bo Liang, Chen Gong, Wei Gao, Chenren Xu ·

    Wave2Body:将毫米波人体姿态估计重新构想为雷达到身体的Token翻译

    arXiv:2607.18875v1 Announce Type: new Abstract: Millimeter-wave (mmWave) radar enables privacy-friendly human sensing, but its sparse point clouds are physical measurements of view-dependent electromagnetic reflections and only indirectly characterize body articulation. Recoverin…