I have been playing around the algorithm with tensorflow in this paper. I tried to convert a photo to a Chinese ink and wash painring, but I got some strange patterns in the output picture(those in the top left corner). I totally followed the algorithm in the paper except that I add another loss term for total variation denoising. I have some confusions about this:
In the paper it used the 16-layer vgg net. I am going to try some other networks, such as googlenet or alexnet. But I was wondering whether it would avoid these patterns if I use some other networks.
In the paper, it used the gram matrix to represent the style loss. But I don't know the reason here. I was also wondering if there's any other way to stand for the style loss.
Since I have used total variation denoising here, and the result is not satisfactory. I was wondering if there're some other ways of denoising to avoid these patterns.
(I'm sorry that I can't upload my content input image because I don't have enough reputation in stack overflow as a new user. If you're interested, you can search the google image with"Shanghai Jiaotong university" and find the original image there.)