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The facial landmarks can provide valuable information for expression-related tasks. However, most approaches only use landmarks for segmentation preprocessing or directly input them into the neural network for fully connection. Such simple combination not only fails to pass the spatial information to network, but also increases calculation amounts. The method proposed in this paper aims to integrate facial landmarks-driven representation into the triplet network. The spatial information provided... 相似文献
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