A Comparative Study of Graph Matching Algorithms in Computer Vision

Benchmark Results for “car8”

This page shows the benchmarks results for the dataset instance “car8”. We consider solutions as optimal if the objective value is within a 0.1% range of the known optimum -44.

Run time 1s

method value bound optimal accuracy
dd-ls0 -43.9987 -43.9993 yes 84.62%
dd-ls3 -30.5471 -51.5504 no 46.15%
dd-ls4 -27.9173 -55.6253 no 19.23%
fgmd inf -inf no
fm-bca -43.9987 -49.5758 yes 84.62%
fm -43.9987 -81.524 yes 84.62%
fw -34.2828 -inf no 7.69%
ga -43.5125 -inf no 80.77%
hbp inf -inf no
ipfps -38.5152 -inf no 50.00%
ipfpu -31.5582 -inf no 46.15%
lsm -33.9719 -inf no 23.08%
mp -43.9987 -48.8474 yes 84.62%
mp-fw -43.9987 -48.291 yes 84.62%
mpm -34.7667 -inf no 46.15%
mp-mcf -41.7227 -47.8189 no 80.77%
pm -25.6289 -inf no 7.69%
rrwm -40.4392 -inf no 38.46%
sm -40.0274 -inf no 65.38%
smac -37.0641 -inf no 53.85%

Run time 10s

method value bound optimal accuracy
dd-ls0 -43.9987 -43.9993 yes 84.62%
dd-ls3 -43.9987 -43.9988 yes 84.62%
dd-ls4 -32.858 -47.3967 no 30.77%
fgmd -43.9987 -inf yes 84.62%
fm-bca -43.9987 -49.5758 yes 84.62%
fm -43.9987 -81.524 yes 84.62%
fw -34.2828 -inf no 7.69%
ga -43.5125 -inf no 80.77%
hbp -43.7763 -50.0474 no 69.23%
ipfps -38.5152 -inf no 50.00%
ipfpu -31.5582 -inf no 46.15%
lsm -33.9719 -inf no 23.08%
mp -43.9987 -48.8474 yes 84.62%
mp-fw -43.9987 -45.2854 yes 84.62%
mpm -34.7667 -inf no 46.15%
mp-mcf -43.9987 -44.9014 yes 84.62%
pm -25.6289 -inf no 7.69%
rrwm -40.4392 -inf no 38.46%
sm -40.0274 -inf no 65.38%
smac -37.0641 -inf no 53.85%

Run time 100s

method value bound optimal accuracy
dd-ls0 -43.9987 -43.9993 yes 84.62%
dd-ls3 -43.9987 -43.9988 yes 84.62%
dd-ls4 -43.9987 -43.9987 yes 84.62%
fgmd -43.9987 -inf yes 84.62%
fm-bca -43.9987 -49.5758 yes 84.62%
fm -43.9987 -81.524 yes 84.62%
fw -34.2828 -inf no 7.69%
ga -43.5125 -inf no 80.77%
hbp -43.7763 -50.0474 no 69.23%
ipfps -38.5152 -inf no 50.00%
ipfpu -31.5582 -inf no 46.15%
lsm -33.9719 -inf no 23.08%
mp -43.9987 -48.8474 yes 84.62%
mp-fw -43.9987 -44.1702 yes 84.62%
mpm -34.7667 -inf no 46.15%
mp-mcf -43.9987 -44.0806 yes 84.62%
pm -25.6289 -inf no 7.69%
rrwm -40.4392 -inf no 38.46%
sm -40.0274 -inf no 65.38%
smac -37.0641 -inf no 53.85%

Run time 300s

method value bound optimal accuracy
dd-ls0 -43.9987 -43.9993 yes 84.62%
dd-ls3 -43.9987 -43.9988 yes 84.62%
dd-ls4 -43.9987 -43.9987 yes 84.62%
fgmd -43.9987 -inf yes 84.62%
fm-bca -43.9987 -49.5758 yes 84.62%
fm -43.9987 -81.524 yes 84.62%
fw -34.2828 -inf no 7.69%
ga -43.5125 -inf no 80.77%
hbp -43.7763 -50.0474 no 69.23%
ipfps -38.5152 -inf no 50.00%
ipfpu -31.5582 -inf no 46.15%
lsm -33.9719 -inf no 23.08%
mp -43.9987 -48.8474 yes 84.62%
mp-fw -43.9987 -44.1561 yes 84.62%
mpm -34.7667 -inf no 46.15%
mp-mcf -43.9987 -44.0217 yes 84.62%
pm -25.6289 -inf no 7.69%
rrwm -40.4392 -inf no 38.46%
sm -40.0274 -inf no 65.38%
smac -37.0641 -inf no 53.85%

Other Results for this Dataset

Accumulated results for whole dataset: car

Results for individual instances of the dataset: