对比的自我监督的表现学习,没有负样本,用于多式模式的人类行动识别

Huaigang Yang1, Ziliang Ren1,2, Huaqiang Yuan1

  • 1School of Computer Science and Technology, Dongguan University of Technology, Dongguan, China.

PubMed
概括

这项研究引入了使用多式联络数据 (如骨架序列和IMU信号) 进行动作识别的新框架. 该方法提高了不需要负样本的性能,在各种学习场景中提高了准确性.

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