3S-Net: arbitrary semantic-aware style transfer - Bingqing Guo
2021 Intelligent Sensing Winter School
3S-Net: arbitrary semantic-aware style transfer
Bingqing Guo, Queen Mary University of London
A cluster of stunning style transfer approaches evolve to include single style transfer and multi-style transfer these years. However, few studies consider the style consistency between identical semantic objects in style images and the content image respectively. Especially for multi-style transfer, the merged style is obtained through a simple linear combination with given weights. So, the textures of each source style are mixed, which makes the result lack aesthetic value. To overcome this problem, I would like to introduce a 3S-Net to achieve semantic-aware style transfer mainly by Two-Step Semantic Instance Normalization (2SSIN) and Semantic Style Swap.
Slides: http://cis.eecs.qmul.ac.uk/2021Winter...
As part of the 2021 Intelligent Sensing Winter School: http://cis.eecs.qmul.ac.uk/school2021...