pdfcoffee

Advanced Convolutional Neural Networks
For instance, go to https://deepart.io/ and see a cool demo as shown in the
following image, where DeepArt has been applied by taking the "Van Gogh"
style as observed in the Sunflowers painting and applying it to a picture of my
daughter Aurora:
Now, how can we define more formally the process of style transfer? Well, style
transfer is the task of producing an artificial image x that shares the content of
a source content image p and the style of a source style image a. So, intuitively
we need two distance functions: one distance function measures how different the
content of two images is, L content
, while the other distance function measures how
different the style of two images is, L style
. Then, the transfer style can be seen as an
optimization problem where we try to minimize these two metrics. As in Leon A.
Gatys, Alexander S. Ecker, Matthias Bethge [7], we use a pretrained network to
achieve style transfer. In particular, we can feed a VGG19 (or any suitable pretrained
network) for extracting features that represent images in an efficient way. Now we
are going to define two functions used for training the network: the content distance
and the style distance.
Content distance
Given two images, p content image and x input image, we define the content
distance as the distance in the feature space defined by a layer l for a VGG19 network
receiving the two images as an input. In other words, the two images are represented
by the features extracted by a pretrained VGG19. These features project the images
into a feature "content" space where the "content" distance can be conveniently
computed as follows:
[ 166 ]