A Comparative Study of Graph Matching Algorithms in Computer Vision

Benchmark Results for “car26”

This page shows the benchmarks results for the dataset instance “car26”. We consider solutions as optimal if the objective value is within a 0.1% range of the known optimum -59.92.

Run time 1s

method value bound optimal accuracy
dd-ls0 -59.9239 -59.9457 yes 89.66%
dd-ls3 -54.184 -61.4392 no 82.76%
dd-ls4 -47.2955 -67.576 no 58.62%
fgmd inf -inf no
fm-bca -59.9239 -59.9239 yes 89.66%
fm -59.9239 -94.3981 yes 89.66%
fw -57.2328 -inf no 72.41%
ga -59.6194 -inf no 79.31%
hbp -59.9239 -62.6105 yes 89.66%
ipfps -59.6194 -inf no 79.31%
ipfpu -46.4863 -inf no 55.17%
lsm -48.109 -inf no 51.72%
mp -59.9239 -59.9239 yes 89.66%
mp-fw -59.9239 -60.0032 yes 89.66%
mpm -51.9316 -inf no 65.52%
mp-mcf -59.9239 -59.9662 yes 89.66%
pm -29.094 -inf no 20.69%
rrwm -59.6194 -inf no 79.31%
sm -53.8541 -inf no 75.86%
smac -52.4575 -inf no 65.52%

Run time 10s

method value bound optimal accuracy
dd-ls0 -59.9239 -59.9457 yes 89.66%
dd-ls3 -59.9239 -59.9246 yes 89.66%
dd-ls4 -59.9239 -60.0454 yes 89.66%
fgmd -59.9239 -inf yes 89.66%
fm-bca -59.9239 -59.9239 yes 89.66%
fm -59.9239 -94.3981 yes 89.66%
fw -57.2328 -inf no 72.41%
ga -59.6194 -inf no 79.31%
hbp -59.9239 -62.6105 yes 89.66%
ipfps -59.6194 -inf no 79.31%
ipfpu -46.4863 -inf no 55.17%
lsm -48.109 -inf no 51.72%
mp -59.9239 -59.9239 yes 89.66%
mp-fw -59.9239 -59.9239 yes 89.66%
mpm -51.9316 -inf no 65.52%
mp-mcf -59.9239 -59.9239 yes 89.66%
pm -29.094 -inf no 20.69%
rrwm -59.6194 -inf no 79.31%
sm -53.8541 -inf no 75.86%
smac -52.4575 -inf no 65.52%

Run time 100s

method value bound optimal accuracy
dd-ls0 -59.9239 -59.9457 yes 89.66%
dd-ls3 -59.9239 -59.9246 yes 89.66%
dd-ls4 -59.9239 -59.9248 yes 89.66%
fgmd -59.9239 -inf yes 89.66%
fm-bca -59.9239 -59.9239 yes 89.66%
fm -59.9239 -94.3981 yes 89.66%
fw -57.2328 -inf no 72.41%
ga -59.6194 -inf no 79.31%
hbp -59.9239 -62.6105 yes 89.66%
ipfps -59.6194 -inf no 79.31%
ipfpu -46.4863 -inf no 55.17%
lsm -48.109 -inf no 51.72%
mp -59.9239 -59.9239 yes 89.66%
mp-fw -59.9239 -59.9239 yes 89.66%
mpm -51.9316 -inf no 65.52%
mp-mcf -59.9239 -59.9239 yes 89.66%
pm -29.094 -inf no 20.69%
rrwm -59.6194 -inf no 79.31%
sm -53.8541 -inf no 75.86%
smac -52.4575 -inf no 65.52%

Run time 300s

method value bound optimal accuracy
dd-ls0 -59.9239 -59.9457 yes 89.66%
dd-ls3 -59.9239 -59.9246 yes 89.66%
dd-ls4 -59.9239 -59.9248 yes 89.66%
fgmd -59.9239 -inf yes 89.66%
fm-bca -59.9239 -59.9239 yes 89.66%
fm -59.9239 -94.3981 yes 89.66%
fw -57.2328 -inf no 72.41%
ga -59.6194 -inf no 79.31%
hbp -59.9239 -62.6105 yes 89.66%
ipfps -59.6194 -inf no 79.31%
ipfpu -46.4863 -inf no 55.17%
lsm -48.109 -inf no 51.72%
mp -59.9239 -59.9239 yes 89.66%
mp-fw -59.9239 -59.9239 yes 89.66%
mpm -51.9316 -inf no 65.52%
mp-mcf -59.9239 -59.9239 yes 89.66%
pm -29.094 -inf no 20.69%
rrwm -59.6194 -inf no 79.31%
sm -53.8541 -inf no 75.86%
smac -52.4575 -inf no 65.52%

Other Results for this Dataset

Accumulated results for whole dataset: car

Results for individual instances of the dataset: