A Comparative Study of Graph Matching Algorithms in Computer Vision

Benchmark Results for “car11”

This page shows the benchmarks results for the dataset instance “car11”. We consider solutions as optimal if the objective value is within a 0.1% range of the known optimum -63.06.

Run time 1s

method value bound optimal accuracy
dd-ls0 -63.0601 -63.0768 yes 100.00%
dd-ls3 -63.0601 -63.0611 yes 100.00%
dd-ls4 -54.669 -64.6561 no 88.89%
fgmd inf -inf no
fm-bca -63.0601 -63.0601 yes 100.00%
fm -63.0601 -87.6327 yes 100.00%
fw -61.901 -inf no 92.59%
ga -63.0601 -inf yes 100.00%
hbp -63.0601 -63.9666 yes 100.00%
ipfps -61.3627 -inf no 92.59%
ipfpu -61.3627 -inf no 92.59%
lsm -56.8569 -inf no 85.19%
mp -63.0601 -63.0601 yes 100.00%
mp-fw -63.0601 -63.0601 yes 100.00%
mpm -56.6066 -inf no 85.19%
mp-mcf -63.0601 -63.0601 yes 100.00%
pm -28.4343 -inf no 14.81%
rrwm -63.0601 -inf yes 100.00%
sm -61.3627 -inf no 92.59%
smac -39.1243 -inf no 48.15%

Run time 10s

method value bound optimal accuracy
dd-ls0 -63.0601 -63.0768 yes 100.00%
dd-ls3 -63.0601 -63.0611 yes 100.00%
dd-ls4 -63.0601 -63.0671 yes 100.00%
fgmd -63.0601 -inf yes 100.00%
fm-bca -63.0601 -63.0601 yes 100.00%
fm -63.0601 -87.6327 yes 100.00%
fw -61.901 -inf no 92.59%
ga -63.0601 -inf yes 100.00%
hbp -63.0601 -63.9666 yes 100.00%
ipfps -61.3627 -inf no 92.59%
ipfpu -61.3627 -inf no 92.59%
lsm -56.8569 -inf no 85.19%
mp -63.0601 -63.0601 yes 100.00%
mp-fw -63.0601 -63.0601 yes 100.00%
mpm -56.6066 -inf no 85.19%
mp-mcf -63.0601 -63.0601 yes 100.00%
pm -28.4343 -inf no 14.81%
rrwm -63.0601 -inf yes 100.00%
sm -61.3627 -inf no 92.59%
smac -39.1243 -inf no 48.15%

Run time 100s

method value bound optimal accuracy
dd-ls0 -63.0601 -63.0768 yes 100.00%
dd-ls3 -63.0601 -63.0611 yes 100.00%
dd-ls4 -63.0601 -63.0671 yes 100.00%
fgmd -63.0601 -inf yes 100.00%
fm-bca -63.0601 -63.0601 yes 100.00%
fm -63.0601 -87.6327 yes 100.00%
fw -61.901 -inf no 92.59%
ga -63.0601 -inf yes 100.00%
hbp -63.0601 -63.9666 yes 100.00%
ipfps -61.3627 -inf no 92.59%
ipfpu -61.3627 -inf no 92.59%
lsm -56.8569 -inf no 85.19%
mp -63.0601 -63.0601 yes 100.00%
mp-fw -63.0601 -63.0601 yes 100.00%
mpm -56.6066 -inf no 85.19%
mp-mcf -63.0601 -63.0601 yes 100.00%
pm -28.4343 -inf no 14.81%
rrwm -63.0601 -inf yes 100.00%
sm -61.3627 -inf no 92.59%
smac -39.1243 -inf no 48.15%

Run time 300s

method value bound optimal accuracy
dd-ls0 -63.0601 -63.0768 yes 100.00%
dd-ls3 -63.0601 -63.0611 yes 100.00%
dd-ls4 -63.0601 -63.0671 yes 100.00%
fgmd -63.0601 -inf yes 100.00%
fm-bca -63.0601 -63.0601 yes 100.00%
fm -63.0601 -87.6327 yes 100.00%
fw -61.901 -inf no 92.59%
ga -63.0601 -inf yes 100.00%
hbp -63.0601 -63.9666 yes 100.00%
ipfps -61.3627 -inf no 92.59%
ipfpu -61.3627 -inf no 92.59%
lsm -56.8569 -inf no 85.19%
mp -63.0601 -63.0601 yes 100.00%
mp-fw -63.0601 -63.0601 yes 100.00%
mpm -56.6066 -inf no 85.19%
mp-mcf -63.0601 -63.0601 yes 100.00%
pm -28.4343 -inf no 14.81%
rrwm -63.0601 -inf yes 100.00%
sm -61.3627 -inf no 92.59%
smac -39.1243 -inf no 48.15%

Other Results for this Dataset

Accumulated results for whole dataset: car

Results for individual instances of the dataset: