Saliency Maps

What are saliency maps?

Saliency maps aims to display what part of the input is the most important part for a model. It tries to do so by trying to maximize the input (with respect to an classifier output). For example, we have a picture of a panda, and our model tells us so. To generate a saliency map, we try to maximize the label panda by modifying the input. If we In other words, a saliency map is generated by trying to maximize the chance of the picture being classified. Most of the time, we use the gradient ascent algorithm to achieve this.