SOTAVerified

RGB Salient Object Detection

RGB Salient object detection is a task-based on a visual attention mechanism, in which algorithms aim to explore objects or regions more attentive than the surrounding areas on the scene or RGB images.

( Image credit: Attentive Feedback Network for Boundary-Aware Salient Object Detection )

Papers

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Showing 1–10 of 222 papers

TitleStatusHype
Patch-Depth Fusion: Dichotomous Image Segmentation via Fine-Grained Patch Strategy and Depth Integrity-PriorCode1
CPDR: Towards Highly-Efficient Salient Object Detection via Crossed Post-decoder Refinement—0
CoLA: Conditional Dropout and Language-driven Robust Dual-modal Salient Object DetectionCode1
Bilateral Reference for High-Resolution Dichotomous Image SegmentationCode7
M^3Net: Multilevel, Mixed and Multistage Attention Network for Salient Object DetectionCode1
Revisiting Image Pyramid Structure for High Resolution Salient Object DetectionCode3
A Weakly Supervised Learning Framework for Salient Object Detection via Hybrid LabelsCode1
Pyramid Grafting Network for One-Stage High Resolution Saliency DetectionCode1
TRACER: Extreme Attention Guided Salient Object Tracing NetworkCode1
C^4Net: Contextual Compression and Complementary Combination Network for Salient Object Detection—0
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All datasetsDUTS-TEDUT-OMRONECSSDHKU-ISHRSODPASCAL-SDAVIS-SUHRSDISTDSBU / SBU-RefineSOCUCF

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1scGANBalanced Error Rate11.5—Unverified
2JDRBalanced Error Rate11.23—Unverified
3DSSBalanced Error Rate10.56—Unverified
4DSCBalanced Error Rate8.1—Unverified
5BMPMBalanced Error Rate8.09—Unverified
6NLDFBalanced Error Rate7.69—Unverified
7CPDBalanced Error Rate7.21—Unverified