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Salient Object Detection On Hku Is 1

Metrics

MAE

Results

Performance results of various models on this benchmark

Paper Title
U2Net0.031U$^2$-Net: Going Deeper with Nested U-Structure for Salient Object Detection
F3Net0.028F3Net: Fusion, Feedback and Focus for Salient Object Detection
LDF0.027Label Decoupling Framework for Salient Object Detection
RCSB0.027Recursive Contour Saliency Blending Network for Accurate Salient Object Detection
SelfReformer0.024SelfReformer: Self-Refined Network with Transformer for Salient Object Detection
EVPv10.024Explicit Visual Prompting for Low-Level Structure Segmentations
SelfReformer-Swin0.023SelfReformer: Self-Refined Network with Transformer for Salient Object Detection
SAM2-UNet0.019SAM2-UNet: Segment Anything 2 Makes Strong Encoder for Natural and Medical Image Segmentation
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Salient Object Detection On Hku Is 1 | SOTA | HyperAI