A Comparative Study of Graph Matching Algorithms in Computer Vision

Benchmark Results for “house-sparse94”

This page shows the benchmarks results for the dataset instance “house-sparse94”. We consider solutions as optimal if the objective value is within a 0.1% range of the known optimum -69.4388.

Run time 1s

method value bound optimal accuracy
dd-ls0 -69.4388 -69.4529 yes 100.00%
dd-ls3 -69.4388 -69.4423 yes 100.00%
dd-ls4 -69.4388 -71.3125 yes 100.00%
fgmd inf -inf no
fm-bca -69.4388 -69.4388 yes 100.00%
fm -69.4388 -78.8858 yes 100.00%
fw 0 -inf no 0.00%
ga -69.4388 -inf yes 100.00%
hbp -69.4388 -69.4388 yes 100.00%
ipfps -69.4388 -inf yes 100.00%
ipfpu -69.4388 -inf yes 100.00%
lsm -69.4388 -inf yes 100.00%
mp -69.4388 -69.4388 yes 100.00%
mp-fw -69.4388 -69.4388 yes 100.00%
mpm -64.565 -inf no 90.00%
mp-mcf -69.4388 -69.4388 yes 100.00%
pm -58.55 -inf no 86.67%
rrwm -69.4388 -inf yes 100.00%
sm -69.4388 -inf yes 100.00%
smac -51.3638 -inf no 83.33%

Run time 10s

method value bound optimal accuracy
dd-ls0 -69.4388 -69.4529 yes 100.00%
dd-ls3 -69.4388 -69.4423 yes 100.00%
dd-ls4 -69.4388 -69.4435 yes 100.00%
fgmd -69.4388 -inf yes 100.00%
fm-bca -69.4388 -69.4388 yes 100.00%
fm -69.4388 -78.8858 yes 100.00%
fw 0 -inf no 0.00%
ga -69.4388 -inf yes 100.00%
hbp -69.4388 -69.4388 yes 100.00%
ipfps -69.4388 -inf yes 100.00%
ipfpu -69.4388 -inf yes 100.00%
lsm -69.4388 -inf yes 100.00%
mp -69.4388 -69.4388 yes 100.00%
mp-fw -69.4388 -69.4388 yes 100.00%
mpm -64.565 -inf no 90.00%
mp-mcf -69.4388 -69.4388 yes 100.00%
pm -58.55 -inf no 86.67%
rrwm -69.4388 -inf yes 100.00%
sm -69.4388 -inf yes 100.00%
smac -51.3638 -inf no 83.33%

Run time 100s

method value bound optimal accuracy
dd-ls0 -69.4388 -69.4529 yes 100.00%
dd-ls3 -69.4388 -69.4423 yes 100.00%
dd-ls4 -69.4388 -69.4435 yes 100.00%
fgmd -69.4388 -inf yes 100.00%
fm-bca -69.4388 -69.4388 yes 100.00%
fm -69.4388 -78.8858 yes 100.00%
fw 0 -inf no 0.00%
ga -69.4388 -inf yes 100.00%
hbp -69.4388 -69.4388 yes 100.00%
ipfps -69.4388 -inf yes 100.00%
ipfpu -69.4388 -inf yes 100.00%
lsm -69.4388 -inf yes 100.00%
mp -69.4388 -69.4388 yes 100.00%
mp-fw -69.4388 -69.4388 yes 100.00%
mpm -64.565 -inf no 90.00%
mp-mcf -69.4388 -69.4388 yes 100.00%
pm -58.55 -inf no 86.67%
rrwm -69.4388 -inf yes 100.00%
sm -69.4388 -inf yes 100.00%
smac -51.3638 -inf no 83.33%

Run time 300s

method value bound optimal accuracy
dd-ls0 -69.4388 -69.4529 yes 100.00%
dd-ls3 -69.4388 -69.4423 yes 100.00%
dd-ls4 -69.4388 -69.4435 yes 100.00%
fgmd -69.4388 -inf yes 100.00%
fm-bca -69.4388 -69.4388 yes 100.00%
fm -69.4388 -78.8858 yes 100.00%
fw 0 -inf no 0.00%
ga -69.4388 -inf yes 100.00%
hbp -69.4388 -69.4388 yes 100.00%
ipfps -69.4388 -inf yes 100.00%
ipfpu -69.4388 -inf yes 100.00%
lsm -69.4388 -inf yes 100.00%
mp -69.4388 -69.4388 yes 100.00%
mp-fw -69.4388 -69.4388 yes 100.00%
mpm -64.565 -inf no 90.00%
mp-mcf -69.4388 -69.4388 yes 100.00%
pm -58.55 -inf no 86.67%
rrwm -69.4388 -inf yes 100.00%
sm -69.4388 -inf yes 100.00%
smac -51.3638 -inf no 83.33%

Other Results for this Dataset

Accumulated results for whole dataset: house-sparse

Results for individual instances of the dataset: