الرئيسية الأخبار أحدث الأوراق البحثية الدروس مجموعات البيانات الموسوعة SOTA نماذج LLM لوحة الأداء GPU الفعاليات

العربية

Salient Object Detection On Pascal S 1

المقاييس

E-measure

MAE

S-measure

max_F1

النتائج

نتائج أداء النماذج المختلفة على هذا المعيار القياسي

اسم النموذج	E-measure	MAE	S-measure	max_F1	Paper Title	Repository
EVPv2	0.917	0.053	0.879	0.869	Explicit Visual Prompting for Universal Foreground Segmentations	-
SelfReformer-Swin	0.874	0.049	0.877	0.896	SelfReformer: Self-Refined Network with Transformer for Salient Object Detection	-
SelfReformer	0.872	0.050	0.874	0.894	SelfReformer: Self-Refined Network with Transformer for Salient Object Detection	-
SAM2-UNet	0.931	0.043	0.894	-	SAM2-UNet: Segment Anything 2 Makes Strong Encoder for Natural and Medical Image Segmentation	-
EVPv1	0.917	0.054	0.878	0.872	Explicit Visual Prompting for Low-Level Structure Segmentations	-
F3Net	0.858	0.061	0.854	0.871	F3Net: Fusion, Feedback and Focus for Salient Object Detection	-
RCSB	0.853	0.059	0.854	0.875	Recursive Contour Saliency Blending Network for Accurate Salient Object Detection	-
F3Net	-	0.086	0.831	0.768	U$^2$-Net: Going Deeper with Nested U-Structure for Salient Object Detection	-
LDF(ours)	0.865	0.059	0.856	0.874	Label Decoupling Framework for Salient Object Detection	-

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Salient Object Detection On Pascal S 1 | SOTA | HyperAI