A Comparative Study of Graph Matching Algorithms in Computer Vision

Benchmark Results for “house-sparse97”

This page shows the benchmarks results for the dataset instance “house-sparse97”. We consider solutions as optimal if the objective value is within a 0.1% range of the known optimum -66.5727.

Run time 1s

method value bound optimal accuracy
dd-ls0 -66.5727 -66.5773 yes 100.00%
dd-ls3 -66.5727 -68.1558 yes 100.00%
dd-ls4 -50.8407 -71.1994 no 83.33%
fgmd inf -inf no
fm-bca -66.5727 -66.5727 yes 100.00%
fm -66.5727 -78.8787 yes 100.00%
fw 0 -inf no 0.00%
ga -66.5727 -inf yes 100.00%
hbp -66.5727 -66.9189 yes 100.00%
ipfps -66.5727 -inf yes 100.00%
ipfpu -66.5727 -inf yes 100.00%
lsm -63.3864 -inf no 93.33%
mp -66.5727 -66.5727 yes 100.00%
mp-fw -66.5727 -66.5727 yes 100.00%
mpm -50.6116 -inf no 83.33%
mp-mcf -66.5727 -66.5727 yes 100.00%
pm -53.6438 -inf no 80.00%
rrwm -66.5727 -inf yes 100.00%
sm -66.5727 -inf yes 100.00%
smac -42.3529 -inf no 66.67%

Run time 10s

method value bound optimal accuracy
dd-ls0 -66.5727 -66.5773 yes 100.00%
dd-ls3 -66.5727 -66.5843 yes 100.00%
dd-ls4 -66.5727 -66.5751 yes 100.00%
fgmd -66.5727 -inf yes 100.00%
fm-bca -66.5727 -66.5727 yes 100.00%
fm -66.5727 -78.8787 yes 100.00%
fw 0 -inf no 0.00%
ga -66.5727 -inf yes 100.00%
hbp -66.5727 -66.9189 yes 100.00%
ipfps -66.5727 -inf yes 100.00%
ipfpu -66.5727 -inf yes 100.00%
lsm -63.3864 -inf no 93.33%
mp -66.5727 -66.5727 yes 100.00%
mp-fw -66.5727 -66.5727 yes 100.00%
mpm -50.6116 -inf no 83.33%
mp-mcf -66.5727 -66.5727 yes 100.00%
pm -53.6438 -inf no 80.00%
rrwm -66.5727 -inf yes 100.00%
sm -66.5727 -inf yes 100.00%
smac -42.3529 -inf no 66.67%

Run time 100s

method value bound optimal accuracy
dd-ls0 -66.5727 -66.5773 yes 100.00%
dd-ls3 -66.5727 -66.5843 yes 100.00%
dd-ls4 -66.5727 -66.5751 yes 100.00%
fgmd -66.5727 -inf yes 100.00%
fm-bca -66.5727 -66.5727 yes 100.00%
fm -66.5727 -78.8787 yes 100.00%
fw 0 -inf no 0.00%
ga -66.5727 -inf yes 100.00%
hbp -66.5727 -66.9189 yes 100.00%
ipfps -66.5727 -inf yes 100.00%
ipfpu -66.5727 -inf yes 100.00%
lsm -63.3864 -inf no 93.33%
mp -66.5727 -66.5727 yes 100.00%
mp-fw -66.5727 -66.5727 yes 100.00%
mpm -50.6116 -inf no 83.33%
mp-mcf -66.5727 -66.5727 yes 100.00%
pm -53.6438 -inf no 80.00%
rrwm -66.5727 -inf yes 100.00%
sm -66.5727 -inf yes 100.00%
smac -42.3529 -inf no 66.67%

Run time 300s

method value bound optimal accuracy
dd-ls0 -66.5727 -66.5773 yes 100.00%
dd-ls3 -66.5727 -66.5843 yes 100.00%
dd-ls4 -66.5727 -66.5751 yes 100.00%
fgmd -66.5727 -inf yes 100.00%
fm-bca -66.5727 -66.5727 yes 100.00%
fm -66.5727 -78.8787 yes 100.00%
fw 0 -inf no 0.00%
ga -66.5727 -inf yes 100.00%
hbp -66.5727 -66.9189 yes 100.00%
ipfps -66.5727 -inf yes 100.00%
ipfpu -66.5727 -inf yes 100.00%
lsm -63.3864 -inf no 93.33%
mp -66.5727 -66.5727 yes 100.00%
mp-fw -66.5727 -66.5727 yes 100.00%
mpm -50.6116 -inf no 83.33%
mp-mcf -66.5727 -66.5727 yes 100.00%
pm -53.6438 -inf no 80.00%
rrwm -66.5727 -inf yes 100.00%
sm -66.5727 -inf yes 100.00%
smac -42.3529 -inf no 66.67%

Other Results for this Dataset

Accumulated results for whole dataset: house-sparse

Results for individual instances of the dataset: