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홈뉴스최신 연구 논문튜토리얼데이터셋백과사전SOTALLM 모델GPU 랭킹컨퍼런스
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Salient Object Detection On Hku Is

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MAE

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이 벤치마크에서 각 모델의 성능 결과

모델 이름
MAE
Paper TitleRepository
TRACER-(ResNet50)0.028TRACER: Extreme Attention Guided Salient Object Tracing Network
CPD-R (ResNet50)0.034Cascaded Partial Decoder for Fast and Accurate Salient Object Detection
TRACER-TE70.020TRACER: Extreme Attention Guided Salient Object Tracing Network
M3Net-S0.019M$^3$Net: Multilevel, Mixed and Multistage Attention Network for Salient Object Detection
UCNet-CVAE0.026Uncertainty Inspired RGB-D Saliency Detection
PoolNet (VGG-16)0.03A Simple Pooling-Based Design for Real-Time Salient Object Detection
C4Net0.025C$^{4}$Net: Contextual Compression and Complementary Combination Network for Salient Object Detection-
DSS (Res2Net-50)0.05Res2Net: A New Multi-scale Backbone Architecture
BASNet0.032BASNet: Boundary-Aware Salient Object Detection-
UCNet-ABP0.027Uncertainty Inspired RGB-D Saliency Detection
InSPyReNet0.028Revisiting Image Pyramid Structure for High Resolution Salient Object Detection
CPDR-L0.028CPDR: Towards Highly-Efficient Salient Object Detection via Crossed Post-decoder Refinement-
M3Net-R0.026M$^3$Net: Multilevel, Mixed and Multistage Attention Network for Salient Object Detection
HybridSOD0.038A Weakly Supervised Learning Framework for Salient Object Detection via Hybrid Labels
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