Cross-Model Distillation of a Human-Pose Foundation Model from Unannotated Infant Video for Markerless 3D Pose Estimation
研究通过从未标注的婴儿视频中进行跨模型蒸馏，提高3D姿态估计模型在婴儿上的表现，解决现有模型在婴儿上不准确的问题。
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Biomechanical 3D Body: Self-Supervised Distillation of Biomechanical Pose from a 3D Body Foundation Model
研究通过在SAM-3D-Body模型上增加一个生物力学预测头，利用自监督蒸馏方法从单张RGB图像中回归出生物力学模型的关节角度和尺度，解决了现有方法输出缺乏生物力学定义的关节角度的问题。
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Portable Biomechanics Laboratory: Clinically Accessible Movement Analysis from a Handheld Smartphone
Clinical practice lacks accessible, objective tools for motor function assessment, hindering the adoption of biomechanical metrics in rehabilitation and neurology. To address this, we propose a portable, smartphone-based monocular video analysis framework: secure video acquisition via mobile devices is coupled with cloud-based computation, high-precision monocular pose estimation, subject-specific biomechanical modeling, and optimization algorithms—enabling clinical-grade full-body kinematic measurement (joint angle error <3°). Our method significantly outperforms patient-reported outcomes (e.g., mJOA), demonstrating high sensitivity and responsiveness to surgical intervention. It reliably quantifies gait parameters and sensitively detects pre- to postoperative functional changes in cervical spondylotic myelopathy. This work represents the first smartphone-video-driven, clinically validated objective assessment of motor function, establishing a standardized pathway for integrating mobile health technologies into evidence-based rehabilitation medicine.
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Cross-Model Distillation of a Human-Pose Foundation Model from Unannotated Infant Video for Markerless 3D Pose Estimation
研究通过从未标注的婴儿视频中进行跨模型蒸馏，提高3D姿态估计模型在婴儿上的表现，解决现有模型在婴儿上不准确的问题。
0 citationsRead paper
Biomechanical 3D Body: Self-Supervised Distillation of Biomechanical Pose from a 3D Body Foundation Model
研究通过在SAM-3D-Body模型上增加一个生物力学预测头，利用自监督蒸馏方法从单张RGB图像中回归出生物力学模型的关节角度和尺度，解决了现有方法输出缺乏生物力学定义的关节角度的问题。
0 citationsRead paper
Portable Biomechanics Laboratory: Clinically Accessible Movement Analysis from a Handheld Smartphone
Clinical practice lacks accessible, objective tools for motor function assessment, hindering the adoption of biomechanical metrics in rehabilitation and neurology. To address this, we propose a portable, smartphone-based monocular video analysis framework: secure video acquisition via mobile devices is coupled with cloud-based computation, high-precision monocular pose estimation, subject-specific biomechanical modeling, and optimization algorithms—enabling clinical-grade full-body kinematic measurement (joint angle error <3°). Our method significantly outperforms patient-reported outcomes (e.g., mJOA), demonstrating high sensitivity and responsiveness to surgical intervention. It reliably quantifies gait parameters and sensitively detects pre- to postoperative functional changes in cervical spondylotic myelopathy. This work represents the first smartphone-video-driven, clinically validated objective assessment of motor function, establishing a standardized pathway for integrating mobile health technologies into evidence-based rehabilitation medicine.
0 citationsRead paper