What can we understand from max-activation generated images?
Those are the activation maps of the learned features. 

In the case of this specific model, the filters learn that the "fishy" parts of the image:


Head-ish and dorsal fin-ish sections that define convex hulls
Scale-ish textures insides the convex hulls and surrounded by water-ish textures outside
Orange-ish and gray-ish colors insides the convex hulls and blue-ish colors outside
The head-ish section tend not to be in the corners of an image (since people frame pictures and people think faces are interesting)