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
Multi-Modal Hybrid Learning and Sequential Training for RGB-T Saliency Detection—0
Learning Noise-Aware Encoder-Decoder from Noisy Labels by Alternating Back-Propagation for Saliency Detection—0
Deeply-Supervised Recurrent Convolutional Neural Network for Saliency Detection—0
Auxiliary Tasks Enhanced Dual-affinity Learning for Weakly Supervised Semantic Segmentation—0
Deep Level Sets for Salient Object Detection—0
Deep Learning for Object Saliency Detection and Image Segmentation—0
Automatic Salient Object Detection for Panoramic Images Using Region Growing and Fixation Prediction Model—0
Multi-Scale Saliency Detection using Dictionary Learning—0
Non-rigid Object Tracking via Deep Multi-scale Spatial-temporal Discriminative Saliency Maps—0
Deep Learning for Light Field Saliency Detection—0
Adaptive Partial Differential Equation Learning for Visual Saliency Detection—0
Learning Background Invariance Improves Generalization and Robustness in Self-Supervised Learning on ImageNet and Beyond—0
Joint Attention-Guided Feature Fusion Network for Saliency Detection of Surface Defects—0
A Unified Two-Stage Group Semantics Propagation and Contrastive Learning Network for Co-Saliency Detection—0
Low-Rate Semantic Communication with Codebook-based Conditional Generative Models—0
Learning Optimal Seeds for Diffusion-based Salient Object Detection—0
DeepACG: Co-Saliency Detection via Semantic-Aware Contrast Gromov-Wasserstein Distance—0
Instance-Level Salient Object Segmentation—0
Learning to Detect Instance-level Salient Objects Using Complementary Image Labels—0
Learning to Detect Salient Objects With Image-Level Supervision—0
All in One: RGB, RGB-D, and RGB-T Salient Object Detection—0
Learning to Predict Saliency on Face Images—0
LooseCut: Interactive Image Segmentation with Loosely Bounded Boxes—0
DeepSaliency: Multi-Task Deep Neural Network Model for Salient Object Detection—0
Inducing Stronger Object Representations in Deep Visual Trackers—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