A Comparative Study of Graph Matching Algorithms in Computer Vision

Benchmark Results for “house-sparse65”

This page shows the benchmarks results for the dataset instance “house-sparse65”. We consider solutions as optimal if the objective value is within a 0.1% range of the known optimum -67.0447.

Run time 1s

method value bound optimal accuracy
dd-ls0 -67.0447 -67.0723 yes 100.00%
dd-ls3 -67.0447 -67.0449 yes 100.00%
dd-ls4 -53.339 -72.3899 no 80.00%
fgmd inf -inf no
fm-bca -67.0447 -67.0447 yes 100.00%
fm -67.0447 -78.8638 yes 100.00%
fw 0 -inf no 0.00%
ga -67.0447 -inf yes 100.00%
hbp -67.0447 -67.4015 yes 100.00%
ipfps -67.0447 -inf yes 100.00%
ipfpu -67.0447 -inf yes 100.00%
lsm -67.0447 -inf yes 100.00%
mp -67.0447 -67.0447 yes 100.00%
mp-fw -67.0447 -67.0447 yes 100.00%
mpm -62.2802 -inf no 90.00%
mp-mcf -67.0447 -67.0447 yes 100.00%
pm -52.6827 -inf no 80.00%
rrwm -67.0447 -inf yes 100.00%
sm -60.4413 -inf no 93.33%
smac -45.1513 -inf no 73.33%

Run time 10s

method value bound optimal accuracy
dd-ls0 -67.0447 -67.0723 yes 100.00%
dd-ls3 -67.0447 -67.0449 yes 100.00%
dd-ls4 -67.0447 -67.0531 yes 100.00%
fgmd -67.0447 -inf yes 100.00%
fm-bca -67.0447 -67.0447 yes 100.00%
fm -67.0447 -78.8638 yes 100.00%
fw 0 -inf no 0.00%
ga -67.0447 -inf yes 100.00%
hbp -67.0447 -67.4015 yes 100.00%
ipfps -67.0447 -inf yes 100.00%
ipfpu -67.0447 -inf yes 100.00%
lsm -67.0447 -inf yes 100.00%
mp -67.0447 -67.0447 yes 100.00%
mp-fw -67.0447 -67.0447 yes 100.00%
mpm -62.2802 -inf no 90.00%
mp-mcf -67.0447 -67.0447 yes 100.00%
pm -52.6827 -inf no 80.00%
rrwm -67.0447 -inf yes 100.00%
sm -60.4413 -inf no 93.33%
smac -45.1513 -inf no 73.33%

Run time 100s

method value bound optimal accuracy
dd-ls0 -67.0447 -67.0723 yes 100.00%
dd-ls3 -67.0447 -67.0449 yes 100.00%
dd-ls4 -67.0447 -67.0531 yes 100.00%
fgmd -67.0447 -inf yes 100.00%
fm-bca -67.0447 -67.0447 yes 100.00%
fm -67.0447 -78.8638 yes 100.00%
fw 0 -inf no 0.00%
ga -67.0447 -inf yes 100.00%
hbp -67.0447 -67.4015 yes 100.00%
ipfps -67.0447 -inf yes 100.00%
ipfpu -67.0447 -inf yes 100.00%
lsm -67.0447 -inf yes 100.00%
mp -67.0447 -67.0447 yes 100.00%
mp-fw -67.0447 -67.0447 yes 100.00%
mpm -62.2802 -inf no 90.00%
mp-mcf -67.0447 -67.0447 yes 100.00%
pm -52.6827 -inf no 80.00%
rrwm -67.0447 -inf yes 100.00%
sm -60.4413 -inf no 93.33%
smac -45.1513 -inf no 73.33%

Run time 300s

method value bound optimal accuracy
dd-ls0 -67.0447 -67.0723 yes 100.00%
dd-ls3 -67.0447 -67.0449 yes 100.00%
dd-ls4 -67.0447 -67.0531 yes 100.00%
fgmd -67.0447 -inf yes 100.00%
fm-bca -67.0447 -67.0447 yes 100.00%
fm -67.0447 -78.8638 yes 100.00%
fw 0 -inf no 0.00%
ga -67.0447 -inf yes 100.00%
hbp -67.0447 -67.4015 yes 100.00%
ipfps -67.0447 -inf yes 100.00%
ipfpu -67.0447 -inf yes 100.00%
lsm -67.0447 -inf yes 100.00%
mp -67.0447 -67.0447 yes 100.00%
mp-fw -67.0447 -67.0447 yes 100.00%
mpm -62.2802 -inf no 90.00%
mp-mcf -67.0447 -67.0447 yes 100.00%
pm -52.6827 -inf no 80.00%
rrwm -67.0447 -inf yes 100.00%
sm -60.4413 -inf no 93.33%
smac -45.1513 -inf no 73.33%

Other Results for this Dataset

Accumulated results for whole dataset: house-sparse

Results for individual instances of the dataset: