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Partial Multi-Label Learning on Image (Average Precision)

82Average Precision

PML-MA

Updated 6d ago

Evaluation Results

Method	Links
PML-MA 2026.04		82
PML-PLR 2026.04		81
PML-ND 2026.04		80.5
PAMB 2026.04		79.8
PML-MA 2026.04		79.5
FBD-PML 2026.04		79
P-LENFN 2026.04		78
PML-PLR 2026.04		77
PML-NI 2026.04		77
PML-ND 2026.04		76.5
FBD-PML 2026.04		75.5
PAMB 2026.04		74.8
P-LENFN 2026.04		74.7
PARTICLE 2026.04		74.3
PML-NI 2026.04		73.2
PML-MA 2026.04		73
PARTICLE 2026.04		72.5
PML-PLR 2026.04		72
PML-ND 2026.04		71.5
PAMB 2026.04		71.1
FBD-PML 2026.04		70
PML-fp 2026.04		68.8
PML-fp 2026.04		67.2
P-LENFN 2026.04		67.1
PARTICLE 2026.04		66.8
PML-NI 2026.04		65.3
PML-fp 2026.04		57.3
WSC-PML 2026.04		0.814
PAMB 2026.04		0.798
WSC-PML 2026.04		0.792
PML-LENFN 2026.04		0.78
FBD-PML 2026.04		0.775
NLR 2026.04		0.772
PML-NI 2026.04		0.77
WSC-PML 2026.04		0.754
PAMB 2026.04		0.748
PML-LENFN 2026.04		0.747
FBD-PML 2026.04		0.743
PML-NI 2026.04		0.732
NLR 2026.04		0.724
PAMB 2026.04		0.711
PML-fp 2026.04		0.688
PML-fp 2026.04		0.672
PML-LENFN 2026.04		0.671
FBD-PML 2026.04		0.669
PML-NI 2026.04		0.653
NLR 2026.04		0.648
PML-fp 2026.04		0.573