SOTAVerified

Saliency Detection

Saliency Detection is a preprocessing step in computer vision which aims at finding salient objects in an image.

Source: An Unsupervised Game-Theoretic Approach to Saliency Detection

Papers

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Showing 151–175 of 364 papers

TitleStatusHype
Feature Decomposition Based Saliency Detection in Electron Cryo-Tomograms—0
Collaborative Temporal Consistency Learning for Point-supervised Natural Language Video Localization—0
Fast Hybrid Image Retargeting—0
Fast and Accurate Light Field Saliency Detection through Deep Encoding—0
Coarse-to-Fine Salient Object Detection with Low-Rank Matrix Recovery—0
Face Sketch Synthesis via Semantic-Driven Generative Adversarial Network—0
Extracting Human Attention through Crowdsourced Patch Labeling—0
CNN-based RGB-D Salient Object Detection: Learn, Select and Fuse—0
Exploiting the Value of the Center-dark Channel Prior for Salient Object Detection—0
Cluster-Based Point Set Saliency—0
An Unsupervised Game-Theoretic Approach to Saliency Detection—0
A General Framework for Saliency Detection Methods—0
Exploiting Egocentric Object Prior for 3D Saliency Detection—0
Characterness: An Indicator of Text in the Wild—0
Exemplar-Driven Top-Down Saliency Detection via Deep Association—0
Can Image Retrieval help Visual Saliency Detection?—0
A novel graph structure for salient object detection based on divergence background and compact foreground—0
Evaluating saliency scores in point clouds of natural environments by learning surface anomalies—0
Enhancing Protein Predictive Models via Proteins Data Augmentation: A Benchmark and New Directions—0
Encoding Based Saliency Detection for Videos and Images—0
C^4Net: Contextual Compression and Complementary Combination Network for Salient Object Detection—0
A novel attention model for salient structure detection in seismic volumes—0
Edge Preserving and Multi-Scale Contextual Neural Network for Salient Object Detection—0
Bridging Saliency Detection to Weakly Supervised Object Detection Based on Self-paced Curriculum Learning—0
DUT-LFSaliency: Versatile Dataset and Light Field-to-RGB Saliency Detection—0
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All datasetsDUT-OMRONHKU-ISCAT2000DUTS-testECSSDPASCAL ContextPASCAL-S

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1UCFMAE0.12—Unverified
2U2-Net+MAE0.06—Unverified
3U2-NetMAE0.05—Unverified
4LDF(ours)MAE0.05—Unverified
5Pyramid Feature AttentionMAE0.04—Unverified
#ModelMetricClaimedVerifiedStatus
1U2-Net+MAE0.04—Unverified
2Pyramid Feature AttentionMAE0.03—Unverified
3LDF(ours)MAE0.03—Unverified
#ModelMetricClaimedVerifiedStatus
1SUMAUC0.89—Unverified
2EYMOLAUC0.83—Unverified
#ModelMetricClaimedVerifiedStatus
1Pyramid Feature AttentionMAE0.04—Unverified
2PFAN [zhao2019pyramid] (+) PRNMAE0.04—Unverified
#ModelMetricClaimedVerifiedStatus
1Pyramid Feature AttentionMAE0.03—Unverified
#ModelMetricClaimedVerifiedStatus
1InvPTmax_F184.81—Unverified
#ModelMetricClaimedVerifiedStatus
1Pyramid Feature AttentionMAE0.07—Unverified