As my postings in this blog show, I got interested in image processing by neural networks through style transfer, two and half years ago. Style transfer takes two images, a content image and another image to act as a style model, and then recreates the content image using color and …
I have noticed that I prefer the original neural-style over the faster variants like texture-nets and fast-neural-style. One reason is that neural-style allows more control and more immediate feedback when working on images; this applies when one is not interested in developing reusable filters but working a individual images and developing …
New innovative GAN implementations are published every week. A particularly interesting one is CycleGAN, which promises to learn to do transformations, similar to what pix2pix does, but without needing pairs of corresponding images. In other words, it claims to be able to transform horses to zebras using a training set consisting …
In an earlier post, http://liipetti.net/erratic/2016/11/25/imaginary-landscapes-using-pix2pix/, I experimented with pix2pix, a versatile new package for training a model, using a conditional GAN architecture, to do various image transforms. In that earlier post, I also ventured beyond an image transform in which the content of the image is kept spatially similar, namely adding what is …
There is much hype out there concerning style transfer, but there is very little serious discussion about how all this relates to art. There are claims of being able to produce art, or that art as we know it is now past, while it is not at all obvious that …
Pix2pix is a brand-new tool which is intended to allow application-independent training of any kind of image transform. All that is needed is a dataset containing image pairs, A and B, and one can train a network to transform to either direction. Possible applications include colorization, segmentation, line drawing to …
When I found neural style transfer in September 2015, I was not looking for something to instantly convert my photos into works of art, but rather new tools to use within an artistic workflow. This, I think, puts me in a minority amongst neural style transfer users and developers. Before …
A couple of years ago I participated a research project on Adam traditions in different religions from fresh points of view. For my own paper, I proceeded from a story in the Hebrew “Book of Raziel”, which tells how Adam is confused, full of grief and anxiety, when he is …
Neural style transfer, to be able to produce images combining the content of one image with the style of another, emerged roughly one year ago. It all started with a paper by Gatys et al describing a method of using a convolutional neural network augmented by Gram matrices, and very soon there …
I have, in many of my posts, described my experiments using and mis-using neural-style. Some of my experiments can be rather hard to understand in detail unless the reader has a basic understanding how neural-style works. So this post will try to bridge that gap, without going into the mathematical …
