Memories are about the past, but they serve the future. Memory research often emphasizes
the former aspect: focusing on the functions that re-constitute (re-member) experience and …

In humans, Attention is a core property of all perceptual and cognitive operations. Given our
limited ability to process competing sources, attention mechanisms select, modulate, and …

Semantic segmentation assigns a class label to each image pixel. This dense prediction
problem requires large amounts of manually annotated data, which is often unavailable …

Salient object detection has recently witnessed substantial progress due to powerful
features extracted using deep convolutional neural networks (CNNs). However, existing …

We introduce a simple yet surprisingly powerful model to incorporate attention in action
recognition and human object interaction tasks. Our proposed attention module can be …

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 …

Modeling visual attention-particularly stimulus-driven, saliency-based attention-has been a
very active research area over the past 25 years. Many different models of attention are now …

Visual saliency analysis detects salient regions/objects that attract human attention in
natural scenes. It has attracted intensive research in different fields such as computer vision …

Image saliency detection has recently witnessed rapid progress due to deep convolutional
neural networks. However, none of the existing methods is able to identify object instances …

In this paper, we formulate saliency detection via absorbing Markov chain on an image
graph model. We jointly consider the appearance divergence and spatial distribution of …