A Comparative Study of Graph Matching Algorithms in Computer Vision

Benchmark Results for “car18”

This page shows the benchmarks results for the dataset instance “car18”. We consider solutions as optimal if the objective value is within a 0.1% range of the known optimum -92.18.

Run time 1s

method value bound optimal accuracy
dd-ls0 -92.1773 -92.1959 yes 95.00%
dd-ls3 -77.7238 -94.7273 no 80.00%
dd-ls4 -60.1569 -96.8113 no 65.00%
fgmd inf -inf no
fm-bca -92.1773 -92.1773 yes 95.00%
fm -92.1773 -133.291 yes 95.00%
fw -92.1773 -inf yes 95.00%
ga -92.1773 -inf yes 95.00%
hbp -92.1773 -92.5942 yes 95.00%
ipfps -88.4549 -inf no 85.00%
ipfpu -85.4974 -inf no 82.50%
lsm -54.461 -inf no 55.00%
mp -92.1773 -92.1773 yes 95.00%
mp-fw -92.1773 -92.1773 yes 95.00%
mpm inf -inf no
mp-mcf -92.1773 -92.1773 yes 95.00%
pm -41.4922 -inf no 27.50%
rrwm -91.7031 -inf no 100.00%
sm -87.6906 -inf no 80.00%
smac -81.524 -inf no 75.00%

Run time 10s

method value bound optimal accuracy
dd-ls0 -92.1773 -92.1959 yes 95.00%
dd-ls3 -92.1773 -92.1883 yes 95.00%
dd-ls4 -85.4502 -93.1827 no 87.50%
fgmd -92.1773 -inf yes 95.00%
fm-bca -92.1773 -92.1773 yes 95.00%
fm -92.1773 -133.291 yes 95.00%
fw -92.1773 -inf yes 95.00%
ga -92.1773 -inf yes 95.00%
hbp -92.1773 -92.5942 yes 95.00%
ipfps -88.4549 -inf no 85.00%
ipfpu -85.4974 -inf no 82.50%
lsm -54.461 -inf no 55.00%
mp -92.1773 -92.1773 yes 95.00%
mp-fw -92.1773 -92.1773 yes 95.00%
mpm -77.1312 -inf no 77.50%
mp-mcf -92.1773 -92.1773 yes 95.00%
pm -41.4922 -inf no 27.50%
rrwm -91.7031 -inf no 100.00%
sm -87.6906 -inf no 80.00%
smac -81.524 -inf no 75.00%

Run time 100s

method value bound optimal accuracy
dd-ls0 -92.1773 -92.1959 yes 95.00%
dd-ls3 -92.1773 -92.1883 yes 95.00%
dd-ls4 -92.1773 -92.1832 yes 95.00%
fgmd -92.1773 -inf yes 95.00%
fm-bca -92.1773 -92.1773 yes 95.00%
fm -92.1773 -133.291 yes 95.00%
fw -92.1773 -inf yes 95.00%
ga -92.1773 -inf yes 95.00%
hbp -92.1773 -92.5942 yes 95.00%
ipfps -88.4549 -inf no 85.00%
ipfpu -85.4974 -inf no 82.50%
lsm -54.461 -inf no 55.00%
mp -92.1773 -92.1773 yes 95.00%
mp-fw -92.1773 -92.1773 yes 95.00%
mpm -77.1312 -inf no 77.50%
mp-mcf -92.1773 -92.1773 yes 95.00%
pm -41.4922 -inf no 27.50%
rrwm -91.7031 -inf no 100.00%
sm -87.6906 -inf no 80.00%
smac -81.524 -inf no 75.00%

Run time 300s

method value bound optimal accuracy
dd-ls0 -92.1773 -92.1959 yes 95.00%
dd-ls3 -92.1773 -92.1883 yes 95.00%
dd-ls4 -92.1773 -92.1832 yes 95.00%
fgmd -92.1773 -inf yes 95.00%
fm-bca -92.1773 -92.1773 yes 95.00%
fm -92.1773 -133.291 yes 95.00%
fw -92.1773 -inf yes 95.00%
ga -92.1773 -inf yes 95.00%
hbp -92.1773 -92.5942 yes 95.00%
ipfps -88.4549 -inf no 85.00%
ipfpu -85.4974 -inf no 82.50%
lsm -54.461 -inf no 55.00%
mp -92.1773 -92.1773 yes 95.00%
mp-fw -92.1773 -92.1773 yes 95.00%
mpm -77.1312 -inf no 77.50%
mp-mcf -92.1773 -92.1773 yes 95.00%
pm -41.4922 -inf no 27.50%
rrwm -91.7031 -inf no 100.00%
sm -87.6906 -inf no 80.00%
smac -81.524 -inf no 75.00%

Other Results for this Dataset

Accumulated results for whole dataset: car

Results for individual instances of the dataset: