1. A method for generating a system for predicting saliency in an image, comprising: for each of a set of training images: generating an attention map; and representing the attention map as a first probability distribution which includes, for each of a set of pixels, a respective value corresponding to a probability of the pixel being fixated upon; and with a processor, training a neural network to output a saliency map for an input image, the training including updating parameters of the neural network to optimize an objective function over the training set, the objective function being based on a distance measure computed between a second probability distribution computed for a saliency map output by the neural network, given an input training image, and the first probability distribution computed for the attention map of the respective training image, the second probability distribution including, for each of the set of pixels, a respective probability.