  This work tackles the Pixel Privacy task put forth by MediaEval 2019. Our
goal is to manipulate images in a way that conceals them from automatic scene
classifiers while preserving the original image quality. We use the fast
gradient sign method, which normally has a corrupting influence on image
appeal, and devise two methods to minimize the damage. The first approach uses
a map of pixel locations that are either salient or flat, and directs
perturbations away from them. The second approach subtracts the gradient of an
aesthetics evaluation model from the gradient of the attack model to guide the
perturbations towards a direction that preserves appeal. We make our code
available at: https://git.io/JesXr.
