5 citations · 5 across the 1 of their papers we have counts for
3 papers
cs.CV2022★ 5 cited
Cross-Domain Style Mixing for Face Cartoonization
Seungkwon Kim, Chaeheon Gwak, Dohyun Kim +4
Cartoon domain has recently gained increasing popularity. Previous studies have attempted quality portrait stylization into the cartoon domain; however, this poses a great challeng…
cs.CV2019
Unsupervised Image-to-Image Translation with Self-Attention Networks
Taewon Kang, Kwang Hee Lee
Unsupervised image translation aims to learn the transformation from a source domain to another target domain given unpaired training data. Several state-of-the-art works have yiel…
cs.CV2018
Arbitrary Style Transfer with Style-Attentional Networks
Dae Young Park, Kwang Hee Lee
Arbitrary style transfer aims to synthesize a content image with the style of an image to create a third image that has never been seen before. Recent arbitrary style transfer algo…