Name
Title | ||
|---|---|---|
Graph Convolutional Network with Structure Pooling and Joint-wise Channel Attention for Action Recognition |
Abstract | ||
|---|---|---|
•We propose a novel structure based graph pooling (SGP) scheme to gradually expand the receptivefields of graph convolution kernels in deeper layers, which can enhance the ability of GCNs for extracting more global motion information and bring a reduction in the amount of parameters and computation cost.•We propose a joint-wise channel attention (JCA) module to mine discriminative information among confusing actions with attention mechanism, which shows significant improvement for classifying confusion actions.•Experimental results demonstrate that our model outperforms the existing state-of-the-art methods. |
Year | DOI | Venue |
|---|---|---|
2020 | 10.1016/j.patcog.2020.107321 | Pattern Recognition |
Keywords | DocType | Volume |
Graph convolutional network,Structure graph pooling,Joint-wise channel attention | Journal | 103 |
Issue | ISSN | Citations |
1 | 0031-3203 | 3 |
PageRank | References | Authors |
0.37 | 0 | 7 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Yuxin Chen | 1 | 3 | 0.71 |
| Gaoqun Ma | 2 | 3 | 0.37 |
| Chunfeng Yuan | 3 | 418 | 30.84 |
| Li Bing | 4 | 54 | 2.75 |
| Hui Zhang | 5 | 104 | 7.12 |
| Fangshi Wang | 6 | 21 | 4.74 |
| Weiming Hu | 7 | 5300 | 261.38 |