Deep-learning (DL) algorithms are becoming the standard for processing ultrasound (US)
fetal images. A number of survey papers in the field is today available, but most of them are …

Abstract Models of gaze allocation in complex scenes are derived mainly from studies of
static picture viewing. The dominant framework to emerge has been image salience, where …

Camouflage is a key defence mechanism across species that is critical to survival. Common
camouflage include background matching, imitating the color and pattern of the …

We propose to forecast future hand-object interactions given an egocentric video. Instead of
predicting action labels or pixels, we directly predict the hand motion trajectory and the …

Data-driven saliency has recently gained a lot of attention thanks to the use of convolutional
neural networks for predicting gaze fixations. In this paper, we go beyond standard …

Zero-shot learning (ZSL) aims to recognize novel classes by transferring semantic
knowledge from seen classes to unseen classes. Since semantic knowledge is built on …

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 …

How best to evaluate a saliency model's ability to predict where humans look in images is an
open research question. The choice of evaluation metric depends on how saliency is …

Understanding where people look in images is an important problem in computer vision.
Despite significant research, it remains unclear to what extent human fixations can be …

Understanding and predicting the human visual attention mechanism is an active area of
research in the fields of neuroscience and computer vision. In this paper, we propose …