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 …
Salicon: Saliency in context
Saliency in Context (SALICON) is an ongoing effort that aims at understanding and
predicting visual attention. This paper presents a new method to collect large-scale human …
predicting visual attention. This paper presents a new method to collect large-scale human …
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 …
Quantitative analysis of human-model agreement in visual saliency modeling: A comparative study
Visual attention is a process that enables biological and machine vision systems to select
the most relevant regions from a scene. Relevance is determined by two components: 1) top …
the most relevant regions from a scene. Relevance is determined by two components: 1) top …
Saliency prediction in the deep learning era: Successes and limitations
A Borji - IEEE transactions on pattern analysis and machine …, 2019 - ieeexplore.ieee.org
Visual saliency models have enjoyed a big leap in performance in recent years, thanks to
advances in deep learning and large scale annotated data. Despite enormous effort and …
advances in deep learning and large scale annotated data. Despite enormous effort and …
A deep spatial contextual long-term recurrent convolutional network for saliency detection
Traditional saliency models usually adopt hand-crafted image features and human-
designed mechanisms to calculate local or global contrast. In this paper, we propose a novel …
designed mechanisms to calculate local or global contrast. In this paper, we propose a novel …
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 …
Defending Yarbus: Eye movements reveal observers' task
In a very influential yet anecdotal illustration, Yarbus suggested that human eye-movement
patterns are modulated top down by different task demands. While the hypothesis that it is …
patterns are modulated top down by different task demands. While the hypothesis that it is …
Eml-net: An expandable multi-layer network for saliency prediction
Existing advanced saliency systems have been proposed using Convolutional Neural
Networks (CNNs), the prior knowledge of objectness is crucial for saliency detection …
Networks (CNNs), the prior knowledge of objectness is crucial for saliency detection …
[HTML][HTML] Saccadic model of eye movements for free-viewing condition
In this paper, we propose a new framework to predict visual scanpaths of observers while
they freely watch a visual scene. The visual fixations are inferred from bottom-up saliency …
they freely watch a visual scene. The visual fixations are inferred from bottom-up saliency …