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Salient Object Detection on HKU-IS (test)

0.019MAEM3Net-S
0.01840.022450.02650.03055May 30, 2020Dec 16, 2020Jul 5, 2021Jan 21, 2022Aug 10, 2022Feb 26, 2023Sep 15, 2023

Evaluation results

MethodLinks
M3Net-SArchitecture=Transformer, Backbone=SwinTransformer2023.090.019——0.9430.977—0.937
TE5#Params=31.3M, GFLOPS=11.522021.120.020.952—0.933——0.923
TE7#Params=66.27M, GFLOPS=18.862021.120.020.954—0.932——0.934
BBRF2023.050.02—0.9580.9350.965——
EVPv2Backbone=ViT-SAM2023.050.02—0.9570.9370.966——
BBRFArchitecture=Transformer2023.090.02——0.9320.972—0.932
TE6#Params=43.47M, GFLOPS=14.842021.120.0210.954—0.932——0.932
InSPyReNetBackbone=SwinB2022.090.0210.955—0.944———
Mao et al.Backbone=SwinB2022.090.0220.945—0.934———
ICON-SArchitecture=Transformer, Backbone=SwinTransformer2023.090.022——0.9350.974—0.925
Ours2021.120.023——0.930.96492.2—
TE4#Params=20.71M, GFLOPS=8.642021.120.0230.948—0.925——0.925
F³NetBackbone=SwinB, Re-implementation=true2022.090.0230.944—0.932———
PA-KRNBackbone=SwinB, Re-implementation=true2022.090.0230.944—0.933———
EVPv2Backbone=SegFormer2023.050.023—0.9530.9320.963——
TE3#Params=14.02M, GFLOPS=6.262021.120.0240.944—0.922——0.919
SelfReformer-fullTransformer-based=true, Upsampling Strategy=Pixel Shuffle2022.050.024——0.930.95994.7—
LDFBackbone=SwinB, Re-implementation=true2022.090.0240.941—0.933———
SelfReformer2023.050.024—0.9470.930.959——
EVPv1Backbone=SegFormer2023.050.024—0.9520.9310.961——
C4Net-C5Backbone=ResNet-1012021.100.025—0.931—0.961——
SelfReformer-BITransformer-based=true, Upsampling Strategy=Bilinear Interpolation2022.050.025——0.9280.95694.3—
MINetBackbone=SwinB, Re-implementation=true2022.090.0250.938—0.93———
SRformerArchitecture=Transformer2023.090.025——0.9280.966—0.912
SCNet2021.120.026——0.9270.9691.7—
MSFNetTransformer-based=false2022.050.026——0.9070.95392.7—
PFSNetTransformer-based=false2022.050.026——0.9240.95694.3—
PFSNetArchitecture=CNN2023.090.026——0.9240.962—0.91
M3Net-RArchitecture=CNN, Backbone=ResNet502023.090.026——0.9290.966—0.913
DSANetInput=RGB2020.050.0270.9420.9170.922———
LDFBackbone=ResNet-502021.100.027—0.914—0.954——
C4Net-C4Backbone=ResNet-502021.100.027—0.925—0.956——
TE1#Params=9.96M, GFLOPS=4.282021.120.0270.937—0.916——0.912
TE2#Params=11.09M, GFLOPS=5.22021.120.0270.939—0.918——0.915
LDFTransformer-based=false2022.050.027——0.9190.95393.9—
DCNTransformer-based=false2022.050.027——0.9220.95793.9—
PAKRNTransformer-based=false2022.050.027——0.9230.95494.2—
LDFBackbone=Res2Net50, Re-implementation=true2022.090.0270.935—0.924———
PA-KRNBackbone=Res2Net50, Re-implementation=true2022.090.0270.935—0.922———
InSPyReNetBackbone=Res2Net502022.090.0270.938—0.929———
LDF2023.050.027—0.9390.9190.954——
F3NetInput=RGB2020.050.0280.9370.910.917———
F3NetBackbone=ResNet-502021.100.028—0.912—0.954——
F3Net2021.120.028——0.9170.95291—
LDF2021.120.028——0.920.95391.3—
F3Net#Params=25.54M, GFLOPS=32.862021.120.0280.943—0.917——0.909
LDF#Params=25.15M, GFLOPS=31.022021.120.0280.943—0.919——0.913
TE0#Params=7.45M, GFLOPS=4.262021.120.0280.935—0.913——0.91
F3NetTransformer-based=false2022.050.028——0.9170.95293.6—
MINetTransformer-based=false2022.050.028——0.9180.95393.4—
MINetBackbone=Res2Net50, Re-implementation=true2022.090.0280.931—0.923———
LDFArchitecture=CNN2023.090.028——0.9190.958—0.904
MINetBackbone=ResNet-502021.100.029—0.918—0.959——
MINet#Params=162M, GFLOPS=174.222021.120.0290.942—0.919——0.906
VSTTransformer-based=true2022.050.029——0.9280.95294.2—
GateNetBackbone=ResNeXt1012022.090.0290.932—0.925———
VSTBackbone=T2T-ViT-142022.090.0290.937—0.928———
Chen et al.Backbone=SwinB, Re-implementation=true2022.090.0290.935—0.928———
VST2023.050.029—0.9420.9280.953——
MINet-RArchitecture=CNN, Backbone=ResNet502023.090.029——0.9190.96—0.897
ICON-RArchitecture=CNN, Backbone=ResNet502023.090.029——0.920.96—0.902
VSTArchitecture=Transformer2023.090.029——0.9280.968—0.897
PoolNetBackbone=ResNet-502021.100.03—0.917—0.955——
PoolNet2021.120.03——0.9190.94590.3—
ITSD2021.120.03——0.9210.9590.6—
VST2021.120.03——0.9280.9590.3—
PoolNet#Params=68.21M, GFLOPS=1782021.120.030.944—0.919——0.902
GCPATransformer-based=false2022.050.03——0.920.94993.8—
F³NetBackbone=Res2Net50, Re-implementation=true2022.090.030.925—0.915———
EVPv2Backbone=ViT-CLS2023.050.03—0.9390.9210.947——
EVPv2Backbone=ViT-MAE2023.050.03—0.9390.9220.947——
PoolNetArchitecture=CNN2023.090.03——0.9190.958—0.888
CSF-R2Architecture=CNN, Backbone=Res2Net502023.090.03——0.9210.96—0.891
GCPANetInput=RGB2020.050.0310.9380.8980.92———
EGNetBackbone=ResNet-502021.100.031—0.917—0.956——
GCPANetBackbone=ResNet-502021.100.031—0.917—0.956——
EGNet2021.120.031——0.9170.94390—
EGNet#Params=112M, GFLOPS=240.32021.120.0310.943—0.918——0.902
ITSD#Params=26.47M, GFLOPS=31.922021.120.0310.94—0.917——0.903
U2NetTransformer-based=false2022.050.031——0.9150.94893.5—
PiCANetArchitecture=CNN2023.090.031——0.9050.951—0.89
EGNetArchitecture=CNN2023.090.031——0.9180.958—0.887
ITSD-RArchitecture=CNN, Backbone=ResNet502023.090.031——0.9170.96—0.894
PoolNetInput=RGB2020.050.0320.9330.8990.916———
BASNetInput=RGB2020.050.0320.9280.8950.909———
BASNetBackbone=ResNet-502021.100.032—0.914—0.95——
BASNet2021.120.032——0.9090.94390.3—
BASNet#Params=87.06M, GFLOPS=195.022021.120.0320.929—0.909——0.902
GCPANet#Params=67.06M, GFLOPS=87.982021.120.0320.942—0.92——0.898
BASNetBackbone=ResNet342022.090.0320.919—0.909———
EGNetBackbone=ResNet502022.090.0320.92—0.915———
PoolNet2023.050.032—0.9330.910.949——
BASNetArchitecture=CNN2023.090.032——0.9090.951—0.889
SCRN#Params=25.25M, GFLOPS=30.22021.120.0330.943—0.916——0.895
GateNetTransformer-based=false2022.050.033——0.9150.94993.3—
GateNet-RArchitecture=CNN, Backbone=ResNet502023.090.033——0.9150.955—0.88
CPD-RInput=RGB2020.050.0340.9250.8910.905———
SCRNBackbone=ResNet-502021.100.034—0.917—0.953——
CPDBackbone=ResNet-502021.100.034—0.905—0.948——
CPD2021.120.034——0.9060.93889.2—