A Comparative Study of Graph Matching Algorithms in Computer Vision

Benchmark Results for “car29”

This page shows the benchmarks results for the dataset instance “car29”. We consider solutions as optimal if the objective value is within a 0.1% range of the known optimum -84.31.

Run time 1s

method value bound optimal accuracy
dd-ls0 -84.315 -84.3153 yes 87.50%
dd-ls3 -61.9617 -91.9587 no 67.50%
dd-ls4 -54.2726 -94.8808 no 55.00%
fgmd inf -inf no
fm-bca -84.315 -85.1511 yes 87.50%
fm -84.315 -133.981 yes 87.50%
fw -84.1328 -inf no 95.00%
ga -83.4011 -inf no 90.00%
hbp -84.315 -88.3713 yes 87.50%
ipfps -77.0947 -inf no 77.50%
ipfpu -73.4358 -inf no 65.00%
lsm -67.8349 -inf no 60.00%
mp -84.1328 -85.2735 no 95.00%
mp-fw -84.315 -85.4052 yes 87.50%
mpm -65.5821 -inf no 52.50%
mp-mcf -84.315 -85.2119 yes 87.50%
pm -41.8815 -inf no 17.50%
rrwm -82.8878 -inf no 90.00%
sm -77.8852 -inf no 80.00%
smac -73.9527 -inf no 62.50%

Run time 10s

method value bound optimal accuracy
dd-ls0 -84.315 -84.3153 yes 87.50%
dd-ls3 -84.315 -84.3218 yes 87.50%
dd-ls4 -61.9797 -89.7413 no 70.00%
fgmd -84.315 -inf yes 87.50%
fm-bca -84.315 -85.11 yes 87.50%
fm -84.315 -133.981 yes 87.50%
fw -84.1328 -inf no 95.00%
ga -83.4011 -inf no 90.00%
hbp -84.315 -88.3713 yes 87.50%
ipfps -77.0947 -inf no 77.50%
ipfpu -73.4358 -inf no 65.00%
lsm -67.8349 -inf no 60.00%
mp -84.1328 -85.2445 no 95.00%
mp-fw -84.315 -84.6354 yes 87.50%
mpm -65.5821 -inf no 52.50%
mp-mcf -84.315 -84.6335 yes 87.50%
pm -41.8815 -inf no 17.50%
rrwm -82.8878 -inf no 90.00%
sm -77.8852 -inf no 80.00%
smac -73.9527 -inf no 62.50%

Run time 100s

method value bound optimal accuracy
dd-ls0 -84.315 -84.3153 yes 87.50%
dd-ls3 -84.315 -84.3218 yes 87.50%
dd-ls4 -84.315 -84.3155 yes 87.50%
fgmd -84.315 -inf yes 87.50%
fm-bca -84.315 -85.11 yes 87.50%
fm -84.315 -133.981 yes 87.50%
fw -84.1328 -inf no 95.00%
ga -83.4011 -inf no 90.00%
hbp -84.315 -88.3713 yes 87.50%
ipfps -77.0947 -inf no 77.50%
ipfpu -73.4358 -inf no 65.00%
lsm -67.8349 -inf no 60.00%
mp -84.1328 -85.2445 no 95.00%
mp-fw -84.315 -84.6307 yes 87.50%
mpm -65.5821 -inf no 52.50%
mp-mcf -84.315 -84.6335 yes 87.50%
pm -41.8815 -inf no 17.50%
rrwm -82.8878 -inf no 90.00%
sm -77.8852 -inf no 80.00%
smac -73.9527 -inf no 62.50%

Run time 300s

method value bound optimal accuracy
dd-ls0 -84.315 -84.3153 yes 87.50%
dd-ls3 -84.315 -84.3218 yes 87.50%
dd-ls4 -84.315 -84.3155 yes 87.50%
fgmd -84.315 -inf yes 87.50%
fm-bca -84.315 -85.11 yes 87.50%
fm -84.315 -133.981 yes 87.50%
fw -84.1328 -inf no 95.00%
ga -83.4011 -inf no 90.00%
hbp -84.315 -88.3713 yes 87.50%
ipfps -77.0947 -inf no 77.50%
ipfpu -73.4358 -inf no 65.00%
lsm -67.8349 -inf no 60.00%
mp -84.1328 -85.2445 no 95.00%
mp-fw -84.315 -84.4869 yes 87.50%
mpm -65.5821 -inf no 52.50%
mp-mcf -84.315 -84.528 yes 87.50%
pm -41.8815 -inf no 17.50%
rrwm -82.8878 -inf no 90.00%
sm -77.8852 -inf no 80.00%
smac -73.9527 -inf no 62.50%

Other Results for this Dataset

Accumulated results for whole dataset: car

Results for individual instances of the dataset: