A Comparative Study of Graph Matching Algorithms in Computer Vision

Benchmark Results for “car1”

This page shows the benchmarks results for the dataset instance “car1”. We consider solutions as optimal if the objective value is within a 0.1% range of the known optimum -34.88.

Run time 1s

method value bound optimal accuracy
dd-ls0 -34.8775 -34.8779 yes 78.95%
dd-ls3 -34.8775 -34.8779 yes 78.95%
dd-ls4 -34.5771 -35.491 no 89.47%
fgmd inf -inf no
fm-bca -34.8775 -34.9665 yes 78.95%
fm -34.8775 -53.0412 yes 78.95%
fw -34.4628 -inf no 73.68%
ga -34.8775 -inf yes 78.95%
hbp -34.8775 -36.4186 yes 78.95%
ipfps -34.4207 -inf no 89.47%
ipfpu -26.3775 -inf no 47.37%
lsm -34.3523 -inf no 100.00%
mp -34.8775 -34.8775 yes 78.95%
mp-fw -34.8775 -35.1267 yes 78.95%
mpm -34.3523 -inf no 100.00%
mp-mcf -34.8775 -35.1233 yes 78.95%
pm -19.0681 -inf no 26.32%
rrwm -34.8775 -inf yes 78.95%
sm -32.7068 -inf no 78.95%
smac -34.4207 -inf no 89.47%

Run time 10s

method value bound optimal accuracy
dd-ls0 -34.8775 -34.8779 yes 78.95%
dd-ls3 -34.8775 -34.8779 yes 78.95%
dd-ls4 -34.8775 -34.8808 yes 78.95%
fgmd -34.8775 -inf yes 78.95%
fm-bca -34.8775 -34.9665 yes 78.95%
fm -34.8775 -53.0412 yes 78.95%
fw -34.4628 -inf no 73.68%
ga -34.8775 -inf yes 78.95%
hbp -34.8775 -36.4186 yes 78.95%
ipfps -34.4207 -inf no 89.47%
ipfpu -26.3775 -inf no 47.37%
lsm -34.3523 -inf no 100.00%
mp -34.8775 -34.8775 yes 78.95%
mp-fw -34.8775 -34.8775 yes 78.95%
mpm -34.3523 -inf no 100.00%
mp-mcf -34.8775 -34.8775 yes 78.95%
pm -19.0681 -inf no 26.32%
rrwm -34.8775 -inf yes 78.95%
sm -32.7068 -inf no 78.95%
smac -34.4207 -inf no 89.47%

Run time 100s

method value bound optimal accuracy
dd-ls0 -34.8775 -34.8779 yes 78.95%
dd-ls3 -34.8775 -34.8779 yes 78.95%
dd-ls4 -34.8775 -34.8808 yes 78.95%
fgmd -34.8775 -inf yes 78.95%
fm-bca -34.8775 -34.9665 yes 78.95%
fm -34.8775 -53.0412 yes 78.95%
fw -34.4628 -inf no 73.68%
ga -34.8775 -inf yes 78.95%
hbp -34.8775 -36.4186 yes 78.95%
ipfps -34.4207 -inf no 89.47%
ipfpu -26.3775 -inf no 47.37%
lsm -34.3523 -inf no 100.00%
mp -34.8775 -34.8775 yes 78.95%
mp-fw -34.8775 -34.8775 yes 78.95%
mpm -34.3523 -inf no 100.00%
mp-mcf -34.8775 -34.8775 yes 78.95%
pm -19.0681 -inf no 26.32%
rrwm -34.8775 -inf yes 78.95%
sm -32.7068 -inf no 78.95%
smac -34.4207 -inf no 89.47%

Run time 300s

method value bound optimal accuracy
dd-ls0 -34.8775 -34.8779 yes 78.95%
dd-ls3 -34.8775 -34.8779 yes 78.95%
dd-ls4 -34.8775 -34.8808 yes 78.95%
fgmd -34.8775 -inf yes 78.95%
fm-bca -34.8775 -34.9665 yes 78.95%
fm -34.8775 -53.0412 yes 78.95%
fw -34.4628 -inf no 73.68%
ga -34.8775 -inf yes 78.95%
hbp -34.8775 -36.4186 yes 78.95%
ipfps -34.4207 -inf no 89.47%
ipfpu -26.3775 -inf no 47.37%
lsm -34.3523 -inf no 100.00%
mp -34.8775 -34.8775 yes 78.95%
mp-fw -34.8775 -34.8775 yes 78.95%
mpm -34.3523 -inf no 100.00%
mp-mcf -34.8775 -34.8775 yes 78.95%
pm -19.0681 -inf no 26.32%
rrwm -34.8775 -inf yes 78.95%
sm -32.7068 -inf no 78.95%
smac -34.4207 -inf no 89.47%

Other Results for this Dataset

Accumulated results for whole dataset: car

Results for individual instances of the dataset: