Convolutional neural networks are top-performers on image
classification tasks. Understanding how they make use of
color information in images may be useful for various tasks.
In this paper we analyze the representation learned by a popular
CNN to detect and characterize color-related features.
We confirm the existence of some object- and color-specific
units, as well as the effect of layer-depth on color-sensitivity
and class-invariance.