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Creators/Authors contains: "Qingge, Letu"

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  1. ; ; ; ; ( , The 12th Int’l Symposium on Image and Signal Processing and Analysis (ISPA))
    Skeleton-Based Activity recognition is an active research topic in Computer Vision. In recent years, deep learning methods have been used in this area, including Recurrent Neural Network (RNN)-based, Convolutional Neural Network (CNN)-based and Graph Convolutional Network (GCN)-based approaches. This paper provides a survey of recent work on various Graph Convolutional Network (GCN)-based approaches being applied to Skeleton-Based Activity Recognition. We first introduce the conventional implementation of a GCN. Then methods that address the limitations of conventional GCN's are presented. 
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  2. ; ; ; ; ( , IEEE Access)
  3. ; ; ; ( , International Conference on Wireless Algorithms, Systems, and Applications)
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  4. ; ; ; ; ( , International Conference on Wireless Algorithms, Systems, and Applications)
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