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This paper provides an in-depth study and analysis of human artistic poses through intelligently enhanced multimodal artistic pose recognition. A complementary network model architecture of multimodal information based on motion energy proposed. The network exploits both the rich information of appearance features provided by RGB data and the depth information provided by depth data as well as the characteristics of robustness to luminance and observation angle. The multimodal fusion is accomplished by the complementary information chara
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