Chengyao Shen

SALICON: Reducing the Semantic Gap in Saliency Prediction by Adapting Deep Neural Networks

Saliency in Context (SALICON) is an ongoing effort that aims at understanding and predicting visual attention. Conventional saliency models typically rely on low-level image statistics to predict human fixations. While these models perform significantly better than chance, there is still a large gap…