新的自下而上的视dmits combination with other maps. The model is simple, and biologically plausible insofar as it is naturally parallelized. This model powerfully predicts human xations on 749 variations of 108 natural images, achieving 98% of the ROC area

gbvs_nips 基于图的显著性。Graph-Based Visual Saliency。是发表在2006年NIPS上的论文。(A new bottom-up visual saliency model, Graph-Based Visual Saliency (GBVS), is proposed. It consists of two steps: first forming activation maps on certain feature channels, and then nor