Transductive Zero-Shot Learning with Visual Structure Constraint

NeurIPS 2019 Ziyu WanDongdong ChenYan LiXingguang YanJunge ZhangYizhou YuJing Liao

To recognize objects of the unseen classes, most existing Zero-Shot Learning(ZSL) methods first learn a compatible projection function between the common semantic space and the visual space based on the data of source seen classes, then directly apply it to the target unseen classes. However, in real scenarios, the data distribution between the source and target domain might not match well, thus causing the well-known \textbf{domain shift} problem... (read more)

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