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In this paper, we present saccadic models which are an alternative way to predict where observers look at. Compared to saliency models, saccadic models generate plausible visual scanpaths from which saliency maps can be computed. In addition these models have the advantage of being adaptable to different viewing conditions, viewing tasks and types of visual scene. We demonstrate that saccadic models perform better than existing saliency models for predicting where an observer looks at indoi:10.2352/issn.2470-1173.2016.13.iqsp-216 fatcat:eoglzmrbsjbknjvqvtvsszsuqe