JMM-TGT:通过联合运动掩盖和拓引导变压器实现自我监督的3D动作识别
Han Wen1, Guangping Zeng1, Qingchuan Zhang2
1School of Computer and Communication Engineering, University of Science and Technology Beijing, Beijing, China.
PloS one
|December 30, 2025
概括
本研究介绍了用拓引导变压器 (JMM-TGT) 进行联合运动掩盖的3D骨架动作识别. JMM-TGT模型通过更好地捕捉微妙的关节运动和复杂的时空关系来提高识别准确性.
科学领域:
- 计算机视觉 计算机视觉
- 机器学习 机器学习
- 人工智能的人工智能
背景情况:
- 在3D骨动作识别中的自主监督学习通常集中在单个动作特征上.
- 这种方法限制了捕捉微妙的运动变化和复杂的时空关系,导致不完全的行动理解.
研究的目的:
- 提出一种新型模型,即用拓引导变压器 (JMM-TGT) 进行联合运动掩盖,用于增强3D骨架动作识别.
- 提高模型感知微妙关节运动和捕捉复杂的时空依赖性的能力.
主要方法:
- 实现了联合运动掩盖 (JMM),以基于联合运动差异和相似之处生成掩盖概率,在每个时间步骤中指导联合掩盖.
- 集成了一个拓引导的变压器编码器,该编码器包含关节之间的拓关系,以调整注意力机制,以更好地捕捉时空依赖.
主要成果:
- 在不同的评估设置中,JMM-TGT模型显示了1.5%至7.9%的性能改进.
- 对NTU RGB+D 60,NTU RGB+D 120和PUK-MMD数据集进行了对主流动作识别模型进行比较实验.
结论:
- 拟议的JMM-TGT模型通过解决现有的自我监督方法的局限性,有效地提高了3D骨架动作识别.
- 联合运动掩盖和拓引导注意力的组合显著改善了对人类行为中复杂动态模式的理解.
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