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Moreover, the proposed grouped attention mechanism exploits the hierarchical knowledge within the graph so the GAGCN makes it possible for propagating the visual-semantic connections from seen activities to unseen ones. We thoroughly measure the recommended strategy on three data sets HMDB51, UCF101, and NTU RGB + D. Experimental results show that the GAGCN outperforms advanced methods.We face a binary multiple instance understanding (MIL) problem, whose objective is alwa
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