Yongcheng Jing

Hi, @htoyryla Recently, we propose an approach to exploit one single model to achieve continuous stroke size control after training. With our algorithm, a single trained model can achieve different...

我发邮件第二作者一直没有回复，第一作者回复地很快，几分钟就回我了，不过还是叫我找第二作者发邮件要....

Hi @TJCoding , Thank you so much for your interest in our work. It is a very interesting issue to discuss the transfer of Surrealism style. I agree that current...

@xpeng Here is a recent work which discusses the stroke size problem and also tries to exploit one single model to achieve continuous stroke size control after training: http://yongchengjing.com/StrokeControllable Demo...

Hi, @xpeng Our code as well as pre-trained models which can scale style at testing stage are finally ready: https://github.com/LouieYang/stroke-controllable-fast-style-transfer We have also updated our paper correspondingly at: https://arxiv.org/abs/1802.07101 Welcome...

@xpeng Thanks! On a single NVIDIA Quadro M6000, it takes averagely 0.09s to stylized an image with size 1024*1024. Our code supports the flexible control and the real-time stylization, which...

@xpeng Yes. They have applied this technique to one of their products [Pailitao](http://www.pailitao.com/) to provide users some interesting image processing tools.

Hi @GlebBrykin Great work. I will keep this issue open so that more people can refer to your collection.

Hi @zy-xc Thank you for your interest in our work. Here is the link for the corresponding supplement: https://drive.google.com/file/d/1sBFXqWaWOeMuaaVHMM-ddBssKr3OmutW/view?usp=sharing Please feel free to contact me if there is any other...

Hi @zy-xc Thank you for your interests in our work! Regarding your question, yes, we indeed set group # to be equal to the feature channel, which is indicated in...