Rethinking Knowledge Graph Propagation for Zero-Shot Learning

CVPR 2019 Michael KampffmeyerYinbo ChenXiaodan LiangHao WangYujia ZhangEric P. Xing

Graph convolutional neural networks have recently shown great potential for the task of zero-shot learning. These models are highly sample efficient as related concepts in the graph structure share statistical strength allowing generalization to new classes when faced with a lack of data... (read more)

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