The high volume of visual data usually available for autonomous applications contains information that is mostly irrelevant. Humans perform sensorial filtering through a mechanism called attention. In this work, we present a new fully convolutional neural network designed for detecting visual salience. Experiments carried out with the MIT300 benchmark presented state-of-the-art performance and a parameter reduction of 3/4 compared to similar models.