262 citations · 513 across the 5 of their papers we have counts for
3 papers · 1 filter
DeepGaze II: Reading fixations from deep features trained on object recognition
Matthias Kümmerer, Thomas S. A. Wallis, Matthias Bethge
Here we present DeepGaze II, a model that predicts where people look in images. The model uses the features from the VGG-19 deep neural network trained to identify objects in image…
Deep Gaze I: Boosting Saliency Prediction with Feature Maps Trained on ImageNet
Matthias Kümmerer, Lucas Theis, Matthias Bethge
Recent results suggest that state-of-the-art saliency models perform far from optimal in predicting fixations. This lack in performance has been attributed to an inability to model…
How close are we to understanding image-based saliency?
Matthias Kümmerer, Thomas Wallis, Matthias Bethge
Within the set of the many complex factors driving gaze placement, the properities of an image that are associated with fixations under free viewing conditions have been studied ex…