English(EN) Cross-Modal Action Recognition in Egocentric Video Using Mamba: Integrating RGB and Hand Skeleton Streams via CLS Token Fusion Strategies

基于Mamba的模型融合RGB和骨骼数据用于动作识别

作者 PulseAugur 编辑部 · [1 个来源] · 2026-05-26 04:00

研究人员开发了一种新颖的单目动作识别跨模态架构，使用基于Mamba的框架集成了RGB视频和手部骨骼数据。该方法利用了状态空间模型的线性时间复杂度，并引入了四种用于多模态融合的类别（CLS）Token混合策略。在H2O数据集上的实验表明，‘Average’策略显著提高了准确性，在Tiny配置下比基线提高了10%以上，在Small配置下提高了2%以上。 AI

影响引入了一种新颖的多模态动作识别融合策略，有望提高依赖于单目视频分析的应用的性能。

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arXiv cs.CV TIER_1 English(EN) · Juan Ignacio Bustos Gorostegui, Maria Elena Buemi · 2026-05-26 04:00

使用 Mamba 在自主视频中进行跨模态动作识别：通过 CLS Token 融合策略整合 RGB 和手部骨骼流

arXiv:2605.24302v1 Announce Type: new Abstract: Egocentric action recognition is a challenging task due to erratic camera motion, frequent hand occlusion, and the difficulty of maintaining consistent visual representations over time. In this work, we propose a cross-modal archite…

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使用 Mamba 在自主视频中进行跨模态动作识别：通过 CLS Token 融合策略整合 RGB 和手部骨骼流

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