显著性检测组会汇报ppt，主要讲解了将金字塔特征注意力网络用于显著性检测的方法，网络结构，实验等内容。

Saliency Detection via Graph-Based Manifold Ranking对应的源码

目前来说，显著性检测用MSRA1000基本足够，用于检测单目标算法的准确率和召回率，之后有扩充的MSRA10K，该数据集已公开。

In this paper, we introduce a method to detect co-saliency from an image pair that may have some objects in common. The co-saliency is modeled as a linear combination of the single-image saliency map (SISM) and the multi-image saliency map (MISM). The first term is designed to describe the local attention, which is computed by using three saliency detection techniques available in literature. To compute the MISM, a co-multilayer graph is constructed by dividing the image pair into a spatial pyra

Computing object-based saliency via locality-constrained linear coding and conditional random fields

Image Classification Based on Saliency Coding with Category-specific Codebooks

As a newly emerging and significant topic in computer vision community, co-saliency detection aims at discovering the common salient objects in multiple related images. The existing methods often generate the co-saliency map through a direct forward pipeline which is based on the designed cues or initialization, but lack the refinement-cycle scheme. Moreover, they mainly focus on RGB image and ignore the depth information for RGBD images. In this paper, we propose an iterative RGBD co-saliency f

[亲测可用] Matlab版的显著性检测算法评价指标实现代码,包括AUC_Borji, AUC_Judd, AUC_shuffled(sAUC), CC, EDM, KLDiv, NSS, Similarity. 全部都是亲测可用, 我自己发表的论文也基本上用这些来计算性能.

图像显著性检测，用Saliency算法获得能量图，显示图片的显著性区域 同时显示HSL通道的显著图

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