Salient Object Detection on PASCAL-S

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S-measure

Rank	Model	S-measure	E-measure	MAE	max_F1	Paper	Code	Year
1	FOCUS	0.898	0.942	0.036	–	FOCUS: Towards Universal Foreground Segmentation	geshang777/FOCUS	2025
2	SAM2-UNet	0.894	0.931	0.043	–	SAM2-UNet: Segment Anything 2 Makes Strong Encoder for Natural and Medical Image Segmentation	wzh0120/sam2-unet	2024
3	EVPv2	0.879	0.917	0.053	0.869	Explicit Visual Prompting for Universal Foreground Segmentations	nifangbaage/explict-visual-prompt · nifangbaage/explicit-visual-prompt	2023
4	EVPv1	0.878	0.917	0.054	0.872	Explicit Visual Prompting for Low-Level Structure Segmentations	nifangbaage/explicit-visual-prompt	2023
5	SelfReformer-Swin	0.877	0.874	0.049	0.896	SelfReformer: Self-Refined Network with Transformer for Salient Object Detection	BarCodeReader/SelfReformer	2022
6	SelfReformer	0.874	0.872	0.050	0.894	SelfReformer: Self-Refined Network with Transformer for Salient Object Detection	BarCodeReader/SelfReformer	2022
7	LDF(ours)	0.856	0.865	0.059	0.874	Label Decoupling Framework for Salient Object Detection	weijun88/LDF	2020
8	F3Net	0.854	0.858	0.061	0.871	F3Net: Fusion, Feedback and Focus for Salient Object Detection	weijun88/F3Net · PanoAsh/ASOD60K · PanoAsh/SHD360 · +1	2019
8	RCSB	0.854	0.853	0.059	0.875	Recursive Contour Saliency Blending Network for Accurate Salient Object Detection	BarCodeReader/RCSB-PyTorch	2021
10	F3Net	0.831	–	0.086	0.768	U$^2$-Net: Going Deeper with Nested U-Structure for Salient Object Detection	xuebinqin/U-2-Net · NathanUA/U-2-Net · PaddlePaddle/PaddleSeg · +26	2020