This work tackles the Pixel Privacy task put forth by MediaEval 2019. Our goal is to decrease the accuracy of a classification algorithm 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 that is a combination of salient and flat areas. Perturbations are more noticeable in these locations, and so are directed away from them. The second approach adds the gradient of an aesthetic algorithm to the gradient of the attacking algorithm to guide the perturbations towards a direction that preserves appeal. We make our code available at: https://git.io/JesXr