We build a semantic vector representation of illustrations by training CNNs. As the proposed vector space correctly reflects the semantic meanings of illustrations, users can efficiently search illustrations with similar attributes. In addition, a semantic morphing algorithm that searches the intermediate illustrations that gradually connect two queries is proposed.

Presenter(s)

Yusuke Matsui, The University of Tokyo
Masaki Saito, Tohoku University