CNN-based Style Vector for Style Image Retrieval

In this paper, we have examined the effectiveness of style matrix which is used in the works on style transfer and texture synthesis by Gatys et al. [2, 3] in the context of image retrieval as image features. A style matrix is presented by Gram matrix of the feature maps in a deep convolutional neural network. We proposed a style vector which are generated from a style matrix with PCA dimension reduction. In the experiments, we evaluate image retrieval performance using artistic images downloaded from Wikiarts.org regarding both artistic styles ans artists. We have obtained 40.64% and 70.40% average precision for style search and artist search, respectively, both of which outperformed the results by common CNN features. In addition, we found PCA-compression boosted the performance.