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 251–275 of 364 papers

TitleStatusHype
Unsupervised Video Analysis Based on a Spatiotemporal Saliency Detector—0
Video Saliency Detection by 3D Convolutional Neural Networks—0
Video Smoke Detection Based on Deep Saliency Network—0
Viewport Prediction for Volumetric Video Streaming by Exploring Video Saliency and Trajectory Information—0
ViS-HuD: Using Visual Saliency to Improve Human Detection with Convolutional Neural Networks—0
VISTA: A Visual and Textual Attention Dataset for Interpreting Multimodal Models—0
Visual Saliency Based on Scale-Space Analysis in the Frequency Domain—0
Visual saliency detection: a Kalman filter based approach—0
Visual Saliency Detection in Advanced Driver Assistance Systems—0
Salient Instance Segmentation with Region and Box-level Annotations—0
Weakly-Supervised Saliency Detection via Salient Object Subitizing—0
Weakly-supervised Salient Instance Detection—0
Weakly Supervised Salient Object Detection Using Image Labels—0
WEPSAM: Weakly Pre-Learnt Saliency Model—0
What is a salient object? A dataset and a baseline model for salient object detection—0
When Saliency Meets Sentiment: Understanding How Image Content Invokes Emotion and Sentiment—0
Where's YOUR focus: Personalized Attention—0
PISA: Pixelwise Image Saliency by Aggregating Complementary Appearance Contrast Measures with Edge-Preserving Coherence—0
PISA: Pixelwise Image Saliency by Aggregating Complementary Appearance Contrast Measures with Spatial Priors—0
Point Cloud Quality Assessment using 3D Saliency Maps—0
Quality-Aware Multimodal Saliency Detection via Deep Reinforcement Learning—0
Quantitative Analysis of Saliency Models—0
Recurrent Attentional Networks for Saliency Detection—0
Region-Based Multiscale Spatiotemporal Saliency for Video—0
Region Refinement Network for Salient Object 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