Salicon: Reducing the semantic gap in saliency prediction by adapting deep neural networks
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 …
predicting visual attention. Conventional saliency models typically rely on low-level image …
Salient object detection: A discriminative regional feature integration approach
Salient object detection has been attracting a lot of interest, and recently various heuristic
computational models have been designed. In this paper, we regard saliency map …
computational models have been designed. In this paper, we regard saliency map …
Saliency detection: A boolean map approach
J Zhang, S Sclaroff - … of the IEEE international conference on …, 2013 - cv-foundation.org
A novel Boolean Map based Saliency (BMS) model is proposed. An image is characterized
by a set of binary images, which are generated by randomly thresholding the image's color …
by a set of binary images, which are generated by randomly thresholding the image's color …
Large-scale optimization of hierarchical features for saliency prediction in natural images
Saliency prediction typically relies on hand-crafted (multiscale) features that are combined in
different ways to form a" master" saliency map, which encodes local image conspicuity …
different ways to form a" master" saliency map, which encodes local image conspicuity …
Deep level sets for salient object detection
Deep learning has been applied to saliency detection in recent years. The superior
performance has proved that deep networks can model the semantic properties of salient …
performance has proved that deep networks can model the semantic properties of salient …
Predicting eye fixations using convolutional neural networks
It is believed that eye movements in free-viewing of natural scenes are directed by both
bottom-up visual saliency and top-down visual factors. In this paper, we propose a novel …
bottom-up visual saliency and top-down visual factors. In this paper, we propose a novel …
Analysis of scores, datasets, and models in visual saliency prediction
Significant recent progress has been made in developing high-quality saliency models.
However, less effort has been undertaken on fair assessment of these models, over large …
However, less effort has been undertaken on fair assessment of these models, over large …
Video saliency incorporating spatiotemporal cues and uncertainty weighting
We propose a novel algorithm to detect visual saliency from video signals by combining both
spatial and temporal information and statistical uncertainty measures. The main novelty of …
spatial and temporal information and statistical uncertainty measures. The main novelty of …
End-to-end saliency mapping via probability distribution prediction
Most saliency estimation methods aim to explicitly model low-level conspicuity cues such as
edges or blobs and may additionally incorporate top-down cues using face or text detection …
edges or blobs and may additionally incorporate top-down cues using face or text detection …
Spatiotemporal saliency detection for video sequences based on random walk with restart
A novel saliency detection algorithm for video sequences based on the random walk with
restart (RWR) is proposed in this paper. We adopt RWR to detect spatially and temporally …
restart (RWR) is proposed in this paper. We adopt RWR to detect spatially and temporally …