A Comparative Study of Graph Matching Algorithms in Computer Vision

Benchmark Results for “motor3”

This page shows the benchmarks results for the dataset instance “motor3”. We consider solutions as optimal if the objective value is within a 0.1% range of the known optimum -45.37.

Run time 1s

method value bound optimal accuracy
dd-ls0 -45.375 -45.3932 yes 100.00%
dd-ls3 -45.375 -45.3773 yes 100.00%
dd-ls4 -45.375 -45.8583 yes 100.00%
fgmd inf -inf no
fm-bca -45.375 -45.375 yes 100.00%
fm -45.375 -67.1245 yes 100.00%
fw -43.8727 -inf no 91.30%
ga -44.8294 -inf no 86.96%
hbp -45.375 -46.5108 yes 100.00%
ipfps -44.7886 -inf no 91.30%
ipfpu -42.9834 -inf no 82.61%
lsm -40.8695 -inf no 69.57%
mp -45.375 -45.375 yes 100.00%
mp-fw -45.375 -45.375 yes 100.00%
mpm -27.8706 -inf no 17.39%
mp-mcf -45.375 -45.375 yes 100.00%
pm -23.9838 -inf no 13.04%
rrwm -44.7886 -inf no 91.30%
sm -42.0402 -inf no 82.61%
smac -41.4808 -inf no 69.57%

Run time 10s

method value bound optimal accuracy
dd-ls0 -45.375 -45.3932 yes 100.00%
dd-ls3 -45.375 -45.3773 yes 100.00%
dd-ls4 -45.375 -45.3775 yes 100.00%
fgmd -45.375 -inf yes 100.00%
fm-bca -45.375 -45.375 yes 100.00%
fm -45.375 -67.1245 yes 100.00%
fw -43.8727 -inf no 91.30%
ga -44.8294 -inf no 86.96%
hbp -45.375 -46.5108 yes 100.00%
ipfps -44.7886 -inf no 91.30%
ipfpu -42.9834 -inf no 82.61%
lsm -40.8695 -inf no 69.57%
mp -45.375 -45.375 yes 100.00%
mp-fw -45.375 -45.375 yes 100.00%
mpm -27.8706 -inf no 17.39%
mp-mcf -45.375 -45.375 yes 100.00%
pm -23.9838 -inf no 13.04%
rrwm -44.7886 -inf no 91.30%
sm -42.0402 -inf no 82.61%
smac -41.4808 -inf no 69.57%

Run time 100s

method value bound optimal accuracy
dd-ls0 -45.375 -45.3932 yes 100.00%
dd-ls3 -45.375 -45.3773 yes 100.00%
dd-ls4 -45.375 -45.3775 yes 100.00%
fgmd -45.375 -inf yes 100.00%
fm-bca -45.375 -45.375 yes 100.00%
fm -45.375 -67.1245 yes 100.00%
fw -43.8727 -inf no 91.30%
ga -44.8294 -inf no 86.96%
hbp -45.375 -46.5108 yes 100.00%
ipfps -44.7886 -inf no 91.30%
ipfpu -42.9834 -inf no 82.61%
lsm -40.8695 -inf no 69.57%
mp -45.375 -45.375 yes 100.00%
mp-fw -45.375 -45.375 yes 100.00%
mpm -27.8706 -inf no 17.39%
mp-mcf -45.375 -45.375 yes 100.00%
pm -23.9838 -inf no 13.04%
rrwm -44.7886 -inf no 91.30%
sm -42.0402 -inf no 82.61%
smac -41.4808 -inf no 69.57%

Run time 300s

method value bound optimal accuracy
dd-ls0 -45.375 -45.3932 yes 100.00%
dd-ls3 -45.375 -45.3773 yes 100.00%
dd-ls4 -45.375 -45.3775 yes 100.00%
fgmd -45.375 -inf yes 100.00%
fm-bca -45.375 -45.375 yes 100.00%
fm -45.375 -67.1245 yes 100.00%
fw -43.8727 -inf no 91.30%
ga -44.8294 -inf no 86.96%
hbp -45.375 -46.5108 yes 100.00%
ipfps -44.7886 -inf no 91.30%
ipfpu -42.9834 -inf no 82.61%
lsm -40.8695 -inf no 69.57%
mp -45.375 -45.375 yes 100.00%
mp-fw -45.375 -45.375 yes 100.00%
mpm -27.8706 -inf no 17.39%
mp-mcf -45.375 -45.375 yes 100.00%
pm -23.9838 -inf no 13.04%
rrwm -44.7886 -inf no 91.30%
sm -42.0402 -inf no 82.61%
smac -41.4808 -inf no 69.57%

Other Results for this Dataset

Accumulated results for whole dataset: motor

Results for individual instances of the dataset: