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홈 뉴스 최신 연구 논문 튜토리얼 데이터셋 백과사전 SOTA LLM 모델 GPU 랭킹 컨퍼런스

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Salient Object Detection On Hku Is 1

평가 지표

MAE

평가 결과

이 벤치마크에서 각 모델의 성능 결과

모델 이름	MAE	Paper Title	Repository
U2Net	0.031	U$^2$-Net: Going Deeper with Nested U-Structure for Salient Object Detection	-
LDF	0.027	Label Decoupling Framework for Salient Object Detection	-
SelfReformer	0.024	SelfReformer: Self-Refined Network with Transformer for Salient Object Detection	-
EVPv1	0.024	Explicit Visual Prompting for Low-Level Structure Segmentations	-
SAM2-UNet	0.019	SAM2-UNet: Segment Anything 2 Makes Strong Encoder for Natural and Medical Image Segmentation	-
SelfReformer-Swin	0.023	SelfReformer: Self-Refined Network with Transformer for Salient Object Detection	-
F3Net	0.028	F3Net: Fusion, Feedback and Focus for Salient Object Detection	-
RCSB	0.027	Recursive Contour Saliency Blending Network for Accurate Salient Object Detection	-

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Salient Object Detection On Hku Is 1 | SOTA | HyperAI초신경