Portrait aesthetic quality estimation by semantic complexity

Abstract

In this paper we applied the Caffe convolutional neural networ k (CNN) framework to portrait aesthetics quality estimation. We d esign a set of semantic complexity features extracted from th e intermediate layer features of the CNN architecture. Besides , CNN features trained for different task are compared in aesthe t ic s estimation, and the contribution from content is identifie d .