Computational aesthetics analyzes various expressions arising in art and music works from an aesthetic perspective, and strives to utilize them for the purpose of re-synthesis. Evaluation of such diverse expressions, including exaggeration and omission, is not unified; it does change depending on the intention of the creator and the taste of a person who appreciates the work. This team pursues computational approaches to identification of aesthetic elements.
Members
 ：April enrollment |  ：September enrollment |  ：Team leader |
Research themes
Script Translation in Calligraphic Works Using Deep Learning
Automatic Generation of 3D Natural Anime-like Non-Player Characters with Machine Learning
An Interface for Drawing Effects on 3D Pottery Wheel-type Transparent Canvas