We decided that we wanted to try and reproduce this, and make some convnet art ourselves. To save time, we downloaded the parameters for a trained VGG-16 network. This architecture with 16 trainable layers was proposed by Simonyan et al. and was used to reach the 2nd place in the 2014 ImageNet Large Scale Visual Recognition Challenge. A VGG-16 network primarily consists of convolutional layers with 3-by-3 filters, with the occasional 2-by-2 max-pooling layer in between.
http://317070.github.io/LSD/