Detail-preserving Arbitrary Style Transfer

Style transfer has recently received considerable attention in the academic and industrial field. Recent work has achieved high quality stylized results by using the hidden activation. However, the hierarchy of content image has been mostly ignored. Artistic style factors including texture, stroke sizes or color, also distort, blur, add or remove content details. In this paper, we present a detail-preserving arbitrary style transfer network that can suppress structural distortion and preserve semantic content. We propose a refine network, which can not only spatially match the hierarchical structure but also preserve style patterns. Meanwhile, we introduce the global and local content losses to keep global structure and local detail information, respectively. In addition, our approach is not only effective against detail-preserving arbitrary style transfer, but also friendly with photographic and exposed style transfer. We utilize both quantitative and qualitative evaluations to demonstrate the effectiveness of our method.