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 …
In my two previous posts, I experimented with neural-style by taking the fully connected layers into use. This resulted in something quite different, which I have provisionally called neural-mirage. Neural-mirage looks at the uppermost fc layer, the most abstract classification of what the network thinks it sees in the image, and …
In my previous post, Controlling image content with FC layers, I described how I had modified neural-style to optimize content based on the classifications obtained from the top-most, fully connected layers (which neural-style does not use). I had found that the modified program produced visually quite interesting results, but I …
A few days ago I got an idea to generate images based on fully connected layers of the VGG19 net. As the these layers should contain abstracted information on what the net sees in the input image, perhaps in this way I could make neural-style to generate images based on …
Many people appear to have problems getting neural-style to run, and this is often related to the fact that they try to use it with limited memory such as 2GB. My own tests indicate that neural-style, when used with the default VGG19 network, requires at least 3 GB memory. Lowering …
No, I am not saying that neural networks can achieve everything. The endless possibilities I am facing do not extend outwards towards practical goals. Instead, when I am experimenting with applications of neural network for creative and original art, I am overwhelmed by the endless options and variations at my …
The core of neural-style is the pre-trained neural network. Pre-trained means that the net has been trained using a large number of images, usually with the goal that the net be able to recognize objects and features in images. The default neural network for neural-style, VGG-19 is very effective for …
The big thing about neural-style is being able to separate style and content of an image, and to synthesize new images mixing content and style from different sources. The original paper describing this new technology demonstrated how it is possible to apply the style of famous paintings from Van Gogh, Kandinsky …
In August 2012 I was almost ready with my Ph.D. thesis. The preliminary reviews had been quite positive. I was content and confident about my research as well as about the thesis in its written form. Then the reality of the formalities in waiting struck me. It was not at …
