Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Centrality Graph Convolutional Networks for Skeleton-based Action
  Recognition   The topological structure of skeleton data plays a significant role in human
action recognition. Combining the topological structure with graph
convolutional networks has achieved remarkable performance. In existing
methods, modeling the topological structure of skeleton data only considered
the connections between the joints and bones, and directly use physical
information. However, there exists an unknown problem to investigate the key
joints, bones and body parts in every human action. In this paper, we propose
the centrality graph convolutional networks to uncover the overlooked
topological information, and best take advantage of the information to
distinguish key joints, bones, and body parts. A novel centrality graph
convolutional network firstly highlights the effects of the key joints and
bones to bring a definite improvement. Besides, the topological information of
the skeleton sequence is explored and combined to further enhance the
performance in a four-channel framework. Moreover, the reconstructed graph is
implemented by the adaptive methods on the training process, which further
yields improvements. Our model is validated by two large-scale datasets,
NTU-RGB+D and Kinetics, and outperforms the state-of-the-art methods.

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The categories of this paper are: hep-ph
26
The categories of this paper are: bayes-an
7
The categories of this paper are: hep-th
10
The categories of this paper are: q-bio
18
The categories of this paper are: econ
4
The categories of this paper are: cond-mat
25
The categories of this paper are: patt-sol
22
The categories of this paper are: chao-dyn
9
The categories of this paper are: nlin
12
The categories of this paper are: nucl-th
31
The categories of this paper are: ao-sci
23
The categories of this paper are: solv-int
33
The categories of this paper are: plasm-ph
36
The categories of this paper are: cmp-lg
32
The categories of this paper are: atom-ph
14
The categories of this paper are: math-ph