Abstract Deep Convolutional Neural Networks have been adopted for salient object
detection and achieved the state-of-the-art performance. Most of the previous works …

Recently, deep learning-based methods, especially utilizing fully convolutional neural
networks, have shown extraordinary performance in salient object detection. Despite its …

This paper introduces a Unified Model of Saliency and Importance (UMSI), which learns to
predict visual importance in input graphic designs, and saliency in natural images, along …

For graphical user interface (UI) design, it is important to understand what attracts visual
attention. While previous work on saliency has focused on desktop and web-based UIs …

Desktop notifications should be noticeable but are also subject to a number of design
choices, eg concerning their size, placement, or opacity. It is currently unknown, however …

We propose Unified Model of Saliency and Scanpaths (UMSS)-a model that learns to predict
multi-duration saliency and scanpaths (ie sequences of eye fixations) on information …

With the development of deep learning, salient object detection methods have made great
progress. However, there are still two challenges: 1) The lack of rich features extracted from …

We present a model for predicting visual attention during the free viewing of graphic design
documents. While existing works on this topic have aimed at predicting static saliency of …

When unmanned agricultural vehicles (UAVs) encounter unexpected failures or incidents
during autonomous operations, a highly efficient remote human–machine interaction (HMI) …

The training of the SOD model relies on abundant annotated data, which needs laborious
and expensive manual labeling. The generated pseudo-labels for reducing the annotation of …