Separate to Adapt: Open Set Domain Adaptation via Progressive Separation

CVPR 2019 Hong Liu Zhangjie Cao Mingsheng Long Jianmin Wang Qiang Yang

Domain adaptation has become a resounding success in leveraging labeled data from a source domain to learn an accurate classifier for an unlabeled target domain. When deployed in the wild, the target domain usually contains unknown classes that are not observed in the source domain... (read more)

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