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 301–350 of 364 papers

TitleStatusHype
Saliency Detection via Graph-Based Manifold Ranking—0
Saliency Detection With Fully Convolutional Neural Network—0
Saliency detection with moving camera via background model completion—0
Saliency Detection with Spaces of Background-based Distribution—0
Saliency-Driven Versatile Video Coding for Neural Object Detection—0
Saliency Guided Dictionary Learning for Weakly-Supervised Image Parsing—0
Personalized Saliency and its PredictionCode0
PiCANet: Learning Pixel-wise Contextual Attention for Saliency DetectionCode0
PiCANet: Pixel-wise Contextual Attention Learning for Accurate Saliency DetectionCode0
DeepCO3: Deep Instance Co-Segmentation by Co-Peak Search and Co-Saliency DetectionCode0
Copy-Move Detection in Optical Microscopy: A Segmentation Network and A DatasetCode0
TASED-Net: Temporally-Aggregating Spatial Encoder-Decoder Network for Video Saliency DetectionCode0
PDNet: Prior-model Guided Depth-enhanced Network for Salient Object DetectionCode0
Non-Local Deep Features for Salient Object DetectionCode0
Multi-source weak supervision for saliency detectionCode0
Motion Guided Attention for Video Salient Object DetectionCode0
Object Discovery From a Single Unlabeled Image by Mining Frequent Itemset With Multi-scale FeaturesCode0
Boosting RGB-D Saliency Detection by Leveraging Unlabeled RGB ImagesCode0
Quantitative Analysis of Automatic Image Cropping Algorithms: A Dataset and Comparative StudyCode0
A Stagewise Refinement Model for Detecting Salient Objects in ImagesCode0
Ro-SOS: Metric Expression Network (MEnet) for Robust Salient Object SegmentationCode0
Memory-oriented Decoder for Light Field Salient Object DetectionCode0
Depth-Induced Multi-Scale Recurrent Attention Network for Saliency DetectionCode0
Salient object detection on hyperspectral images using features learned from unsupervised segmentation taskCode0
LOCATE: Self-supervised Object Discovery via Flow-guided Graph-cut and Bootstrapped Self-trainingCode0
PatchRefineNet: Improving Binary Segmentation by Incorporating Signals from Optimal Patch-wise BinarizationCode0
3SD: Self-Supervised Saliency Detection With No LabelsCode0
Light Field Saliency Detection with Deep Convolutional NetworksCode0
A Mutual Learning Method for Salient Object Detection With Intertwined Multi-SupervisionCode0
SaLite : A light-weight model for salient object detectionCode0
Inner and Inter Label Propagation: Salient Object Detection in the WildCode0
Revisiting Saliency Metrics: Farthest-Neighbor Area Under CurveCode0
Learning Uncertain Convolutional Features for Accurate Saliency DetectionCode0
Improving Landmark Recognition using Saliency detection and Feature classificationCode0
SASA: Saliency-Aware Self-Adaptive Snapshot Compressive ImagingCode0
Hyperspectral Image Dataset for Benchmarking on Salient Object DetectionCode0
Learning to Promote Saliency DetectorsCode0
Joint Semantic Mining for Weakly Supervised RGB-D Salient Object DetectionCode0
Hierarchical Cellular Automata for Visual SaliencyCode0
Gravitational Laws of Focus of AttentionCode0
A Plug-and-play Scheme to Adapt Image Saliency Deep Model for Video DataCode0
Joint Learning of Saliency Detection and Weakly Supervised Semantic SegmentationCode0
Unsupervised image saliency detection with Gestalt-laws guided optimization and visual attention based refinementCode0
A Deep Learning Framework for Visual Attention Prediction and Analysis of News InterfacesCode0
Saliency detection based on structural dissimilarity induced by image quality assessment modelCode0
Explainable Image Quality Assessment for Medical ImagingCode0
Saliency Detection by Forward and Backward Cues in Deep-CNNsCode0
ViDSOD-100: A New Dataset and a Baseline Model for RGB-D Video Salient Object DetectionCode0
Towards High-Resolution Salient Object DetectionCode0
Visual Saliency Detection Based on Multiscale Deep CNN FeaturesCode0
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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