A Comparative Study of Graph Matching Algorithms in Computer Vision

Benchmark Results for “house-sparse66”

This page shows the benchmarks results for the dataset instance “house-sparse66”. We consider solutions as optimal if the objective value is within a 0.1% range of the known optimum -64.1649.

Run time 1s

method value bound optimal accuracy
dd-ls0 -64.1649 -64.1746 yes 100.00%
dd-ls3 -64.1649 -64.1809 yes 100.00%
dd-ls4 -49.6005 -69.8556 no 80.00%
fgmd inf -inf no
fm-bca -64.1649 -64.1649 yes 100.00%
fm -64.1649 -78.8627 yes 100.00%
fw 0 -inf no 0.00%
ga -64.1649 -inf yes 100.00%
hbp -64.1649 -65.0165 yes 100.00%
ipfps -64.1649 -inf yes 100.00%
ipfpu -64.1649 -inf yes 100.00%
lsm -61.0422 -inf no 93.33%
mp -64.1649 -64.1649 yes 100.00%
mp-fw -64.1649 -64.1649 yes 100.00%
mpm -43.1164 -inf no 73.33%
mp-mcf -64.1649 -64.1649 yes 100.00%
pm -49.7953 -inf no 80.00%
rrwm -64.1649 -inf yes 100.00%
sm -57.5196 -inf no 93.33%
smac -56.1599 -inf no 93.33%

Run time 10s

method value bound optimal accuracy
dd-ls0 -64.1649 -64.1746 yes 100.00%
dd-ls3 -64.1649 -64.1809 yes 100.00%
dd-ls4 -64.1649 -64.1677 yes 100.00%
fgmd -64.1649 -inf yes 100.00%
fm-bca -64.1649 -64.1649 yes 100.00%
fm -64.1649 -78.8627 yes 100.00%
fw 0 -inf no 0.00%
ga -64.1649 -inf yes 100.00%
hbp -64.1649 -65.0165 yes 100.00%
ipfps -64.1649 -inf yes 100.00%
ipfpu -64.1649 -inf yes 100.00%
lsm -61.0422 -inf no 93.33%
mp -64.1649 -64.1649 yes 100.00%
mp-fw -64.1649 -64.1649 yes 100.00%
mpm -43.1164 -inf no 73.33%
mp-mcf -64.1649 -64.1649 yes 100.00%
pm -49.7953 -inf no 80.00%
rrwm -64.1649 -inf yes 100.00%
sm -57.5196 -inf no 93.33%
smac -56.1599 -inf no 93.33%

Run time 100s

method value bound optimal accuracy
dd-ls0 -64.1649 -64.1746 yes 100.00%
dd-ls3 -64.1649 -64.1809 yes 100.00%
dd-ls4 -64.1649 -64.1677 yes 100.00%
fgmd -64.1649 -inf yes 100.00%
fm-bca -64.1649 -64.1649 yes 100.00%
fm -64.1649 -78.8627 yes 100.00%
fw 0 -inf no 0.00%
ga -64.1649 -inf yes 100.00%
hbp -64.1649 -65.0165 yes 100.00%
ipfps -64.1649 -inf yes 100.00%
ipfpu -64.1649 -inf yes 100.00%
lsm -61.0422 -inf no 93.33%
mp -64.1649 -64.1649 yes 100.00%
mp-fw -64.1649 -64.1649 yes 100.00%
mpm -43.1164 -inf no 73.33%
mp-mcf -64.1649 -64.1649 yes 100.00%
pm -49.7953 -inf no 80.00%
rrwm -64.1649 -inf yes 100.00%
sm -57.5196 -inf no 93.33%
smac -56.1599 -inf no 93.33%

Run time 300s

method value bound optimal accuracy
dd-ls0 -64.1649 -64.1746 yes 100.00%
dd-ls3 -64.1649 -64.1809 yes 100.00%
dd-ls4 -64.1649 -64.1677 yes 100.00%
fgmd -64.1649 -inf yes 100.00%
fm-bca -64.1649 -64.1649 yes 100.00%
fm -64.1649 -78.8627 yes 100.00%
fw 0 -inf no 0.00%
ga -64.1649 -inf yes 100.00%
hbp -64.1649 -65.0165 yes 100.00%
ipfps -64.1649 -inf yes 100.00%
ipfpu -64.1649 -inf yes 100.00%
lsm -61.0422 -inf no 93.33%
mp -64.1649 -64.1649 yes 100.00%
mp-fw -64.1649 -64.1649 yes 100.00%
mpm -43.1164 -inf no 73.33%
mp-mcf -64.1649 -64.1649 yes 100.00%
pm -49.7953 -inf no 80.00%
rrwm -64.1649 -inf yes 100.00%
sm -57.5196 -inf no 93.33%
smac -56.1599 -inf no 93.33%

Other Results for this Dataset

Accumulated results for whole dataset: house-sparse

Results for individual instances of the dataset: