English(EN) PACT: End-to-End Learning of Human Pose, Contacts, and Forces from Video

新模型PACT联合学习视频中的人体姿态、接触点和力

作者 PulseAugur 编辑部 · [1 个来源] · 2026-10-02 04:00

研究人员开发了PACT，一个新颖的端到端模型，旨在从单目视频中联合学习人体姿态、接触点和交互力。该方法将视觉姿态重建与接触和力估计相结合，以期改进联合推理并减少误差传播。PACT利用了时间Transformer和基于物理的监督，并创建了一个名为ForceWall的新数据集，以促进从真实世界攀爬视频中接触力估计的训练和评估。 AI

影响这项研究可能提高视频中人类运动分析的准确性，在体育分析、机器人和虚拟现实领域具有潜在应用。

排序理由这是一篇描述新模型和数据集的研究论文。[lever_c_demoted from research: ic=1 ai=1.0]

在 arXiv cs.AI 阅读 →

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报道来源 [1]

arXiv cs.AI TIER_1 English(EN) · Rikhat Akizhanov (MBZUAI), Yangsong Zhang (MBZUAI), Nikolai Kaliazin (MBZUAI), Peter Wolf (ETH Z\"urich), Yoshihiko Nakamura (MBZUAI), Pascal Fua (EPFL), Fabio Pizzati (MBZUAI), Ivan Laptev (MBZUAI) · 2026-10-02 04:00

PACT：从视频中端到端学习人体姿态、接触和力

arXiv:2610.00451v1 Announce Type: cross Abstract: Human motion, environmental contacts, and interaction forces are governed by common physical laws, yet existing approaches typically separate visual pose reconstruction from contact and force estimation. This separation limits joi…

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报道来源 [1]

PACT：从视频中端到端学习人体姿态、接触和力

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