Trear: Transformer-Based RGB-D Egocentric Action Recognition
IEEE Transactions on Cognitive and Developmental Systems(2022)
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 ...
更多查看译文
关键词
Encoding,Task analysis,Head,Computational modeling,Agriculture,Videos,Standards
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要