%0 Journal Article
%A WU Ming
%A XU Meng-qiu
%A ZHANG Chuang
%A DENG Xiao
%T Adaptive Style Transfer Method of Brocade Crafts Based on Semantic Segmentation
%D 2021
%R 10.13190/j.jbupt.2020-083
%J Journal of Beijing University of Posts and Telecommunications
%P 117-123
%V 44
%N 1
%X Neural style transfer has drawn considerable attention to both academic and art field. However,the existing approaches did not perform so good on brocade style transfer because of its grainy texture and blocky colors which is different from painting. A brocade style transfer approach is proposed that combined semantic segmentation task with adaptive style transfer algorithms by using new content loss and style loss. In addition,in order to solve uneven texture of background in the generated image,Gaussian noise is added to the content image to smoothen background texture during training. It is shown that the proposed approach generates brocade stylization outputs that have high quality as compared with other approaches.
%U https://journal.bupt.edu.cn/EN/10.13190/j.jbupt.2020-083