A Comparative Study of Graph Matching Algorithms in Computer Vision

Benchmark Results for “motor20”

This page shows the benchmarks results for the dataset instance “motor20”. We consider solutions as optimal if the objective value is within a 0.1% range of the known optimum -82.1.

Run time 1s

method value bound optimal accuracy
dd-ls0 -82.0996 -82.1022 yes 94.74%
dd-ls3 -72.6777 -86.0145 no 73.68%
dd-ls4 -56.9583 -91.1751 no 57.89%
fgmd inf -inf no
fm-bca -82.0996 -82.0996 yes 94.74%
fm -82.0996 -124.215 yes 94.74%
fw -81.3199 -inf no 84.21%
ga -82.0996 -inf yes 94.74%
hbp -82.0996 -85.154 yes 94.74%
ipfps -76.9454 -inf no 84.21%
ipfpu -72.5192 -inf no 76.32%
lsm -72.0656 -inf no 76.32%
mp -82.0996 -82.0996 yes 94.74%
mp-fw -82.0996 -82.0996 yes 94.74%
mpm -63.4133 -inf no 60.53%
mp-mcf -82.0996 -82.0996 yes 94.74%
pm -43.7214 -inf no 23.68%
rrwm -81.3199 -inf no 84.21%
sm -74.0803 -inf no 84.21%
smac -56.6141 -inf no 47.37%

Run time 10s

method value bound optimal accuracy
dd-ls0 -82.0996 -82.1022 yes 94.74%
dd-ls3 -82.0996 -82.1029 yes 94.74%
dd-ls4 -80.5605 -84.3492 no 89.47%
fgmd -82.0996 -inf yes 94.74%
fm-bca -82.0996 -82.0996 yes 94.74%
fm -82.0996 -124.215 yes 94.74%
fw -81.3199 -inf no 84.21%
ga -82.0996 -inf yes 94.74%
hbp -82.0996 -85.154 yes 94.74%
ipfps -76.9454 -inf no 84.21%
ipfpu -72.5192 -inf no 76.32%
lsm -72.0656 -inf no 76.32%
mp -82.0996 -82.0996 yes 94.74%
mp-fw -82.0996 -82.0996 yes 94.74%
mpm -63.4133 -inf no 60.53%
mp-mcf -82.0996 -82.0996 yes 94.74%
pm -43.7214 -inf no 23.68%
rrwm -81.3199 -inf no 84.21%
sm -74.0803 -inf no 84.21%
smac -56.6141 -inf no 47.37%

Run time 100s

method value bound optimal accuracy
dd-ls0 -82.0996 -82.1022 yes 94.74%
dd-ls3 -82.0996 -82.1029 yes 94.74%
dd-ls4 -82.0996 -82.1 yes 94.74%
fgmd -82.0996 -inf yes 94.74%
fm-bca -82.0996 -82.0996 yes 94.74%
fm -82.0996 -124.215 yes 94.74%
fw -81.3199 -inf no 84.21%
ga -82.0996 -inf yes 94.74%
hbp -82.0996 -85.154 yes 94.74%
ipfps -76.9454 -inf no 84.21%
ipfpu -72.5192 -inf no 76.32%
lsm -72.0656 -inf no 76.32%
mp -82.0996 -82.0996 yes 94.74%
mp-fw -82.0996 -82.0996 yes 94.74%
mpm -63.4133 -inf no 60.53%
mp-mcf -82.0996 -82.0996 yes 94.74%
pm -43.7214 -inf no 23.68%
rrwm -81.3199 -inf no 84.21%
sm -74.0803 -inf no 84.21%
smac -56.6141 -inf no 47.37%

Run time 300s

method value bound optimal accuracy
dd-ls0 -82.0996 -82.1022 yes 94.74%
dd-ls3 -82.0996 -82.1029 yes 94.74%
dd-ls4 -82.0996 -82.1 yes 94.74%
fgmd -82.0996 -inf yes 94.74%
fm-bca -82.0996 -82.0996 yes 94.74%
fm -82.0996 -124.215 yes 94.74%
fw -81.3199 -inf no 84.21%
ga -82.0996 -inf yes 94.74%
hbp -82.0996 -85.154 yes 94.74%
ipfps -76.9454 -inf no 84.21%
ipfpu -72.5192 -inf no 76.32%
lsm -72.0656 -inf no 76.32%
mp -82.0996 -82.0996 yes 94.74%
mp-fw -82.0996 -82.0996 yes 94.74%
mpm -63.4133 -inf no 60.53%
mp-mcf -82.0996 -82.0996 yes 94.74%
pm -43.7214 -inf no 23.68%
rrwm -81.3199 -inf no 84.21%
sm -74.0803 -inf no 84.21%
smac -56.6141 -inf no 47.37%

Other Results for this Dataset

Accumulated results for whole dataset: motor

Results for individual instances of the dataset: