http://papers.nips.cc/paper_files/paper/2023/file/1e680f115a22d60cbc228a0c6dae5936-Supplemental-Conference.pdf

What Do Deep Saliency Models Learn about Visual Attention? The supplementary materials provide additional results to complement our analyses in the main paper, and elaborate on the implementation details of our visualization method. In the main paper, we visualize the weights of different semantic categories (e.g., action, social, and scene) for saliency prediction in various scenarios. Here we provide complementary results on detailed semantics, which are used to derive the results shown in the main paper (see the listed sections below). In particular, Figure 1 shows the weights of detailed semantics for DINet [1] trained on different datasets (Section 4.2 of the main paper).