毫秒级多视角多人全身姿态重建，速度与泛化能力兼备。
RapidPoseTriangulation: Multi-view Multi-person Whole-body Human Pose Triangulation in a Millisecond
- 基于多视角图像实现快速姿态三角测量
- 支持跨数据集和场景的强泛化性能
- 适用于实时多人全身动作捕捉场景
多视角成像与姿态估计的结合在计算机视觉应用中取得显著进展，为理解人类运动与交互提供了新可能。本文提出一种新算法，提升多视角多人姿态估计效率，重点实现毫秒级三角测量速度与良好泛化能力。方法扩展至全身姿态估计，可捕捉面部表情到手指动作等细节，覆盖多个个体与视角。通过在未见数据集与配置下的优异表现，验证其适应性。相关工作已全部开源，以推动该领域发展。
原文摘要 · Abstract (English)
The integration of multi-view imaging and pose estimation represents a significant advance in computer vision applications, offering new possibilities for understanding human movement and interactions. This work presents a new algorithm that improves multi-view multi-person pose estimation, focusing on fast triangulation speeds and good generalization capabilities. The approach extends to whole-body pose estimation, capturing details from facial expressions to finger movements across multiple individuals and viewpoints. Adaptability to different settings is demonstrated through strong performance across unseen datasets and configurations. To support further progress in this field, all of this work is publicly accessible.
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