A Comparative Study of Graph Matching Algorithms in Computer Vision

Benchmark Results for “house-sparse8”

This page shows the benchmarks results for the dataset instance “house-sparse8”. We consider solutions as optimal if the objective value is within a 0.1% range of the known optimum -65.3787.

Run time 1s

method value bound optimal accuracy
dd-ls0 -65.3787 -65.4149 yes 100.00%
dd-ls3 -65.3787 -65.5039 yes 100.00%
dd-ls4 -48.7935 -71.911 no 76.67%
fgmd inf -inf no
fm-bca -65.3787 -65.3787 yes 100.00%
fm -65.3787 -78.7978 yes 100.00%
fw 0 -inf no 0.00%
ga -65.3787 -inf yes 100.00%
hbp -65.3787 -65.7224 yes 100.00%
ipfps -65.3787 -inf yes 100.00%
ipfpu -65.3787 -inf yes 100.00%
lsm -65.3787 -inf yes 100.00%
mp -65.3787 -65.3787 yes 100.00%
mp-fw -65.3787 -65.3787 yes 100.00%
mpm -60.7517 -inf no 90.00%
mp-mcf -65.3787 -65.3787 yes 100.00%
pm -50.6808 -inf no 83.33%
rrwm -65.3787 -inf yes 100.00%
sm -65.3787 -inf yes 100.00%
smac -65.3787 -inf yes 100.00%

Run time 10s

method value bound optimal accuracy
dd-ls0 -65.3787 -65.4149 yes 100.00%
dd-ls3 -65.3787 -65.5039 yes 100.00%
dd-ls4 -65.3787 -65.3834 yes 100.00%
fgmd -65.3787 -inf yes 100.00%
fm-bca -65.3787 -65.3787 yes 100.00%
fm -65.3787 -78.7978 yes 100.00%
fw 0 -inf no 0.00%
ga -65.3787 -inf yes 100.00%
hbp -65.3787 -65.7224 yes 100.00%
ipfps -65.3787 -inf yes 100.00%
ipfpu -65.3787 -inf yes 100.00%
lsm -65.3787 -inf yes 100.00%
mp -65.3787 -65.3787 yes 100.00%
mp-fw -65.3787 -65.3787 yes 100.00%
mpm -60.7517 -inf no 90.00%
mp-mcf -65.3787 -65.3787 yes 100.00%
pm -50.6808 -inf no 83.33%
rrwm -65.3787 -inf yes 100.00%
sm -65.3787 -inf yes 100.00%
smac -65.3787 -inf yes 100.00%

Run time 100s

method value bound optimal accuracy
dd-ls0 -65.3787 -65.4149 yes 100.00%
dd-ls3 -65.3787 -65.5039 yes 100.00%
dd-ls4 -65.3787 -65.3834 yes 100.00%
fgmd -65.3787 -inf yes 100.00%
fm-bca -65.3787 -65.3787 yes 100.00%
fm -65.3787 -78.7978 yes 100.00%
fw 0 -inf no 0.00%
ga -65.3787 -inf yes 100.00%
hbp -65.3787 -65.7224 yes 100.00%
ipfps -65.3787 -inf yes 100.00%
ipfpu -65.3787 -inf yes 100.00%
lsm -65.3787 -inf yes 100.00%
mp -65.3787 -65.3787 yes 100.00%
mp-fw -65.3787 -65.3787 yes 100.00%
mpm -60.7517 -inf no 90.00%
mp-mcf -65.3787 -65.3787 yes 100.00%
pm -50.6808 -inf no 83.33%
rrwm -65.3787 -inf yes 100.00%
sm -65.3787 -inf yes 100.00%
smac -65.3787 -inf yes 100.00%

Run time 300s

method value bound optimal accuracy
dd-ls0 -65.3787 -65.4149 yes 100.00%
dd-ls3 -65.3787 -65.5039 yes 100.00%
dd-ls4 -65.3787 -65.3834 yes 100.00%
fgmd -65.3787 -inf yes 100.00%
fm-bca -65.3787 -65.3787 yes 100.00%
fm -65.3787 -78.7978 yes 100.00%
fw 0 -inf no 0.00%
ga -65.3787 -inf yes 100.00%
hbp -65.3787 -65.7224 yes 100.00%
ipfps -65.3787 -inf yes 100.00%
ipfpu -65.3787 -inf yes 100.00%
lsm -65.3787 -inf yes 100.00%
mp -65.3787 -65.3787 yes 100.00%
mp-fw -65.3787 -65.3787 yes 100.00%
mpm -60.7517 -inf no 90.00%
mp-mcf -65.3787 -65.3787 yes 100.00%
pm -50.6808 -inf no 83.33%
rrwm -65.3787 -inf yes 100.00%
sm -65.3787 -inf yes 100.00%
smac -65.3787 -inf yes 100.00%

Other Results for this Dataset

Accumulated results for whole dataset: house-sparse

Results for individual instances of the dataset: