A Comparative Study of Graph Matching Algorithms in Computer Vision

Benchmark Results for “house-sparse3”

This page shows the benchmarks results for the dataset instance “house-sparse3”. We consider solutions as optimal if the objective value is within a 0.1% range of the known optimum -65.2456.

Run time 1s

method value bound optimal accuracy
dd-ls0 -65.2456 -65.2506 yes 100.00%
dd-ls3 -65.2456 -65.2482 yes 100.00%
dd-ls4 -48.6807 -72.103 no 76.67%
fgmd inf -inf no
fm-bca -65.2456 -65.2456 yes 100.00%
fm -65.2456 -78.7875 yes 100.00%
fw 0 -inf no 0.00%
ga -65.2456 -inf yes 100.00%
hbp -65.2456 -65.6185 yes 100.00%
ipfps -65.2456 -inf yes 100.00%
ipfpu -65.2456 -inf yes 100.00%
lsm -62.0428 -inf no 93.33%
mp -65.2456 -65.2456 yes 100.00%
mp-fw -65.2456 -65.2456 yes 100.00%
mpm -58.69 -inf no 90.00%
mp-mcf -65.2456 -65.2456 yes 100.00%
pm -50.5355 -inf no 83.33%
rrwm -65.2456 -inf yes 100.00%
sm -65.2456 -inf yes 100.00%
smac -11.7114 -inf no 0.00%

Run time 10s

method value bound optimal accuracy
dd-ls0 -65.2456 -65.2506 yes 100.00%
dd-ls3 -65.2456 -65.2482 yes 100.00%
dd-ls4 -65.2456 -65.4067 yes 100.00%
fgmd -65.2456 -inf yes 100.00%
fm-bca -65.2456 -65.2456 yes 100.00%
fm -65.2456 -78.7875 yes 100.00%
fw 0 -inf no 0.00%
ga -65.2456 -inf yes 100.00%
hbp -65.2456 -65.6185 yes 100.00%
ipfps -65.2456 -inf yes 100.00%
ipfpu -65.2456 -inf yes 100.00%
lsm -62.0428 -inf no 93.33%
mp -65.2456 -65.2456 yes 100.00%
mp-fw -65.2456 -65.2456 yes 100.00%
mpm -58.69 -inf no 90.00%
mp-mcf -65.2456 -65.2456 yes 100.00%
pm -50.5355 -inf no 83.33%
rrwm -65.2456 -inf yes 100.00%
sm -65.2456 -inf yes 100.00%
smac -11.7114 -inf no 0.00%

Run time 100s

method value bound optimal accuracy
dd-ls0 -65.2456 -65.2506 yes 100.00%
dd-ls3 -65.2456 -65.2482 yes 100.00%
dd-ls4 -65.2456 -65.2601 yes 100.00%
fgmd -65.2456 -inf yes 100.00%
fm-bca -65.2456 -65.2456 yes 100.00%
fm -65.2456 -78.7875 yes 100.00%
fw 0 -inf no 0.00%
ga -65.2456 -inf yes 100.00%
hbp -65.2456 -65.6185 yes 100.00%
ipfps -65.2456 -inf yes 100.00%
ipfpu -65.2456 -inf yes 100.00%
lsm -62.0428 -inf no 93.33%
mp -65.2456 -65.2456 yes 100.00%
mp-fw -65.2456 -65.2456 yes 100.00%
mpm -58.69 -inf no 90.00%
mp-mcf -65.2456 -65.2456 yes 100.00%
pm -50.5355 -inf no 83.33%
rrwm -65.2456 -inf yes 100.00%
sm -65.2456 -inf yes 100.00%
smac -11.7114 -inf no 0.00%

Run time 300s

method value bound optimal accuracy
dd-ls0 -65.2456 -65.2506 yes 100.00%
dd-ls3 -65.2456 -65.2482 yes 100.00%
dd-ls4 -65.2456 -65.2601 yes 100.00%
fgmd -65.2456 -inf yes 100.00%
fm-bca -65.2456 -65.2456 yes 100.00%
fm -65.2456 -78.7875 yes 100.00%
fw 0 -inf no 0.00%
ga -65.2456 -inf yes 100.00%
hbp -65.2456 -65.6185 yes 100.00%
ipfps -65.2456 -inf yes 100.00%
ipfpu -65.2456 -inf yes 100.00%
lsm -62.0428 -inf no 93.33%
mp -65.2456 -65.2456 yes 100.00%
mp-fw -65.2456 -65.2456 yes 100.00%
mpm -58.69 -inf no 90.00%
mp-mcf -65.2456 -65.2456 yes 100.00%
pm -50.5355 -inf no 83.33%
rrwm -65.2456 -inf yes 100.00%
sm -65.2456 -inf yes 100.00%
smac -11.7114 -inf no 0.00%

Other Results for this Dataset

Accumulated results for whole dataset: house-sparse

Results for individual instances of the dataset: