用AI实时纠正居家健身动作，让普通人也能拥有私人教练。
FormCoach: Lift Smarter, Not Harder
- 用视觉语言模型分析动作，识别细微错误并实时反馈。
- 在1700段专家标注视频上测试，发现模型表现远低于人类水平。
- 开源数据集和评测工具，推动智能健身教练研究发展。
良好姿势是力量与损伤的关键区别，但居家健身者往往难以获得专业指导。FormCoach将普通摄像头转变为全天候、可交互的AI训练伙伴，利用视觉语言模型（VLMs）实时检测细微动作错误并提供个性化纠正建议。我们通过网页界面展示该能力，并在包含1700对专家标注的用户参考视频的基准数据集上，对当前最先进的VLMs进行评估，覆盖22种力量与柔韧性训练动作。为加速人工智能驱动的健身教练研究，我们发布了数据集及基于评分标准的自动化评估流程，支持模型间的标准化比较。基准测试显示，现有模型与人类教练水平存在显著差距，凸显了将细致、情境感知的动作分析融入交互式AI系统的挑战与机遇。通过将动作纠正视为人机协作与创造的过程，FormCoach开辟了具身智能的新前沿。
原文摘要 · Abstract (English)
Good form is the difference between strength and strain, yet for the fast-growing community of at-home fitness enthusiasts, expert feedback is often out of reach. FormCoach transforms a simple camera into an always-on, interactive AI training partner, capable of spotting subtle form errors and delivering tailored corrections in real time, leveraging vision-language models (VLMs). We showcase this capability through a web interface and benchmark state-of-the-art VLMs on a dataset of 1,700 expert-annotated user-reference video pairs spanning 22 strength and mobility exercises. To accelerate research in AI-driven coaching, we release both the dataset and an automated, rubric-based evaluation pipeline, enabling standardized comparison across models. Our benchmarks reveal substantial gaps compared to human-level coaching, underscoring both the challenges and opportunities in integrating nuanced, context-aware movement analysis into interactive AI systems. By framing form correction as a collaborative and creative process between humans and machines, FormCoach opens a new frontier in embodied AI.
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