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

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 1–25 of 364 papers

TitleStatusHype
U^2-Net: Going Deeper with Nested U-Structure for Salient Object DetectionCode3
A Unified Transformer Framework for Group-based Segmentation: Co-Segmentation, Co-Saliency Detection and Video Salient Object DetectionCode2
InvPT: Inverted Pyramid Multi-task Transformer for Dense Scene UnderstandingCode2
Self-Supervised Transformers for Unsupervised Object Discovery using Normalized CutCode2
SUM: Saliency Unification through Mamba for Visual Attention ModelingCode2
Gradient-Induced Co-Saliency DetectionCode1
Finding Visual Saliency in Continuous Spike StreamCode1
ICNet: Intra-saliency Correlation Network for Co-Saliency DetectionCode1
Deeply supervised salient object detection with short connectionsCode1
CAGNet: Content-Aware Guidance for Salient Object DetectionCode1
Exploring Rich and Efficient Spatial Temporal Interactions for Real Time Video Salient Object DetectionCode1
Few-Cost Salient Object Detection with Adversarial-Paced LearningCode1
Adaptive Graph Convolutional Network with Attention Graph Clustering for Co-saliency DetectionCode1
From Semantic Categories to Fixations: A Novel Weakly-Supervised Visual-Auditory Saliency Detection ApproachCode1
Deep RGB-D Saliency Detection with Depth-Sensitive Attention and Automatic Multi-Modal FusionCode1
A Unified RGB-T Saliency Detection Benchmark: Dataset, Baselines, Analysis and A Novel ApproachCode1
Asymmetric Two-Stream Architecture for Accurate RGB-D Saliency DetectionCode1
AIM 2024 Challenge on Video Saliency Prediction: Methods and ResultsCode1
A2dele: Adaptive and Attentive Depth Distiller for Efficient RGB-D Salient Object DetectionCode1
Object Segmentation Without Labels with Large-Scale Generative ModelsCode1
ConCL: Concept Contrastive Learning for Dense Prediction Pre-training in Pathology ImagesCode1
Simultaneous Image-to-Zero and Zero-to-Noise: Diffusion Models with Analytical Image AttenuationCode1
DFNet: Discriminative feature extraction and integration network for salient object detectionCode1
DS-Net: Dynamic Spatiotemporal Network for Video Salient Object DetectionCode1
Accurate RGB-D Salient Object Detection via Collaborative LearningCode1
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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