  This paper presents abstract art created by neural networks and broadly
recognizable across various computer vision systems. The existence of abstract
forms that trigger specific labels independent of neural architecture or
training set suggests convolutional neural networks build shared visual
representations for the categories they understand. Computer vision classifiers
encountering these drawings often respond with strong responses for specific
labels - in extreme cases stronger than all examples from the validation set.
By surveying human subjects we confirm that these abstract artworks are also
broadly recognizable by people, suggesting visual representations triggered by
these drawings are shared across human and computer vision systems.
