A Comparative Study of Graph Matching Algorithms in Computer Vision

Benchmark Results for “car2”

This page shows the benchmarks results for the dataset instance “car2”. We consider solutions as optimal if the objective value is within a 0.1% range of the known optimum -48.85.

Run time 1s

method value bound optimal accuracy
dd-ls0 -48.8472 -48.8472 yes 79.17%
dd-ls3 -48.8472 -49.0938 yes 79.17%
dd-ls4 -40.2869 -52.3898 no 75.00%
fgmd inf -inf no
fm-bca -48.8472 -49.8225 yes 79.17%
fm -48.8472 -74.1128 yes 79.17%
fw -47.1385 -inf no 62.50%
ga -48.6217 -inf no 75.00%
hbp -48.8472 -52.9778 yes 79.17%
ipfps -45.4184 -inf no 79.17%
ipfpu -45.4184 -inf no 79.17%
lsm -31.2195 -inf no 29.17%
mp -48.8472 -49.9576 yes 79.17%
mp-fw -48.8472 -49.4992 yes 79.17%
mpm -45.9967 -inf no 62.50%
mp-mcf -48.8472 -49.1351 yes 79.17%
pm -29.6128 -inf no 50.00%
rrwm -48.6217 -inf no 75.00%
sm -45.4184 -inf no 79.17%
smac -27.5281 -inf no 25.00%

Run time 10s

method value bound optimal accuracy
dd-ls0 -48.8472 -48.8472 yes 79.17%
dd-ls3 -48.8472 -48.8473 yes 79.17%
dd-ls4 -48.8472 -48.8504 yes 79.17%
fgmd -48.8472 -inf yes 79.17%
fm-bca -48.8472 -49.8224 yes 79.17%
fm -48.8472 -74.1128 yes 79.17%
fw -47.1385 -inf no 62.50%
ga -48.6217 -inf no 75.00%
hbp -48.8472 -52.9778 yes 79.17%
ipfps -45.4184 -inf no 79.17%
ipfpu -45.4184 -inf no 79.17%
lsm -31.2195 -inf no 29.17%
mp -48.8472 -49.9574 yes 79.17%
mp-fw -48.8472 -49.0173 yes 79.17%
mpm -45.9967 -inf no 62.50%
mp-mcf -48.8472 -49.0191 yes 79.17%
pm -29.6128 -inf no 50.00%
rrwm -48.6217 -inf no 75.00%
sm -45.4184 -inf no 79.17%
smac -27.5281 -inf no 25.00%

Run time 100s

method value bound optimal accuracy
dd-ls0 -48.8472 -48.8472 yes 79.17%
dd-ls3 -48.8472 -48.8473 yes 79.17%
dd-ls4 -48.8472 -48.8504 yes 79.17%
fgmd -48.8472 -inf yes 79.17%
fm-bca -48.8472 -49.8224 yes 79.17%
fm -48.8472 -74.1128 yes 79.17%
fw -47.1385 -inf no 62.50%
ga -48.6217 -inf no 75.00%
hbp -48.8472 -52.9778 yes 79.17%
ipfps -45.4184 -inf no 79.17%
ipfpu -45.4184 -inf no 79.17%
lsm -31.2195 -inf no 29.17%
mp -48.8472 -49.9574 yes 79.17%
mp-fw -48.8472 -48.8486 yes 79.17%
mpm -45.9967 -inf no 62.50%
mp-mcf -48.8472 -48.8472 yes 79.17%
pm -29.6128 -inf no 50.00%
rrwm -48.6217 -inf no 75.00%
sm -45.4184 -inf no 79.17%
smac -27.5281 -inf no 25.00%

Run time 300s

method value bound optimal accuracy
dd-ls0 -48.8472 -48.8472 yes 79.17%
dd-ls3 -48.8472 -48.8473 yes 79.17%
dd-ls4 -48.8472 -48.8504 yes 79.17%
fgmd -48.8472 -inf yes 79.17%
fm-bca -48.8472 -49.8224 yes 79.17%
fm -48.8472 -74.1128 yes 79.17%
fw -47.1385 -inf no 62.50%
ga -48.6217 -inf no 75.00%
hbp -48.8472 -52.9778 yes 79.17%
ipfps -45.4184 -inf no 79.17%
ipfpu -45.4184 -inf no 79.17%
lsm -31.2195 -inf no 29.17%
mp -48.8472 -49.9574 yes 79.17%
mp-fw -48.8472 -48.8472 yes 79.17%
mpm -45.9967 -inf no 62.50%
mp-mcf -48.8472 -48.8472 yes 79.17%
pm -29.6128 -inf no 50.00%
rrwm -48.6217 -inf no 75.00%
sm -45.4184 -inf no 79.17%
smac -27.5281 -inf no 25.00%

Other Results for this Dataset

Accumulated results for whole dataset: car

Results for individual instances of the dataset: