Keyword searches are generally used when searching for illustrations of anime characters. However, keyword searches require that the illustrations be tagged first. The illustration information that a tag can express is limited, and it is difficult to search for a specific illustration. We focus on character attributes that are difficult to express using tags. We propose a new search method using the vectorization degrees of character attributes. Accordingly, we first created a character illustration dataset limited to the hair length attribute and then trained a convolutional neural network (CNN) to extract the features. We obtained a vector representation of the character attributes using CNN and confirmed that they could be used for new searches.
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