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Salient Object Detection On Ecssd

Métriques

MAE
mean E-Measure
mean F-Measure

Résultats

Résultats de performance de divers modèles sur ce benchmark

Nom du modèle
MAE
mean E-Measure
mean F-Measure
Paper TitleRepository
CPDR-L0.0330.9510.921CPDR: Towards Highly-Efficient Salient Object Detection via Crossed Post-decoder Refinement-
TRACER-TE70.026-0.940TRACER: Extreme Attention Guided Salient Object Tracing Network-
C4Net0.0290.9570.939C$^{4}$Net: Contextual Compression and Complementary Combination Network for Salient Object Detection-
BASNet0.037--BASNet: Boundary-Aware Salient Object Detection-
DSS (Res2Net-50)0.056--Res2Net: A New Multi-scale Backbone Architecture-
TRACER-(ResNet50)0.033--TRACER: Extreme Attention Guided Salient Object Tracing Network-
M3Net-R0.029--M$^3$Net: Multilevel, Mixed and Multistage Attention Network for Salient Object Detection-
PoolNet (VGG-16)0.038--A Simple Pooling-Based Design for Real-Time Salient Object Detection-
CPD-R (ResNet50)0.037--Cascaded Partial Decoder for Fast and Accurate Salient Object Detection-
M3Net-S0.021--M$^3$Net: Multilevel, Mixed and Multistage Attention Network for Salient Object Detection-
CFDN0.033--Saliency Detection via Global Context Enhanced Feature Fusion and Edge Weighted Loss-
InSPyReNet0.031--Revisiting Image Pyramid Structure for High Resolution Salient Object Detection-
HybridSOD0.051--A Weakly Supervised Learning Framework for Salient Object Detection via Hybrid Labels-
UCNet-CVAE0.035--Uncertainty Inspired RGB-D Saliency Detection-
0 of 14 row(s) selected.
Salient Object Detection On Ecssd | SOTA | HyperAI