Unifying Unsupervised Domain Adaptation and Zero-Shot Visual Recognition

25 Mar 2019Qian WangPenghui BuToby P. Breckon

Unsupervised domain adaptation aims to transfer knowledge from a source domain to a target domain so that the target domain data can be recognized without any explicit labelling information for this domain. One limitation of the problem setting is that testing data, despite having no labels, from the target domain is needed during training, which prevents the trained model being directly applied to classify unseen test instances... (read more)

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