Trear: Transformer-Based RGB-D Egocentric Action Recognition

IEEE Transactions on Cognitive and Developmental Systems(2022)

引用 37|浏览90
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摘要
In this article, we propose a transformer-based RGB-D egocentric action recognition framework, called Trear. It consists of two modules: 1) interframe attention encoder and 2) mutual-attentional fusion block. Instead of using optical flow or recurrent units, we adopt a self-attention mechanism to model the temporal structure of the data from different modalities. Input frames are cropped randomly ...
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关键词
Encoding,Task analysis,Head,Computational modeling,Agriculture,Videos,Standards
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