A Comparative Study of Graph Matching Algorithms in Computer Vision

Benchmark Results for “house-sparse23”

This page shows the benchmarks results for the dataset instance “house-sparse23”. We consider solutions as optimal if the objective value is within a 0.1% range of the known optimum -64.8997.

Run time 1s

method value bound optimal accuracy
dd-ls0 -64.8997 -64.9035 yes 100.00%
dd-ls3 -64.8997 -64.9012 yes 100.00%
dd-ls4 -48.7059 -71.887 no 76.67%
fgmd inf -inf no
fm-bca -64.8997 -64.8997 yes 100.00%
fm -64.8997 -78.7854 yes 100.00%
fw 0 -inf no 0.00%
ga -64.8997 -inf yes 100.00%
hbp -64.8997 -65.3005 yes 100.00%
ipfps -64.8997 -inf yes 100.00%
ipfpu -64.8997 -inf yes 100.00%
lsm -61.7124 -inf no 93.33%
mp -64.8997 -64.8997 yes 100.00%
mp-fw -64.8997 -64.8997 yes 100.00%
mpm -60.3249 -inf no 90.00%
mp-mcf -64.8997 -64.8997 yes 100.00%
pm -52.1421 -inf no 80.00%
rrwm -64.8997 -inf yes 100.00%
sm -64.8997 -inf yes 100.00%
smac -64.8997 -inf yes 100.00%

Run time 10s

method value bound optimal accuracy
dd-ls0 -64.8997 -64.9035 yes 100.00%
dd-ls3 -64.8997 -64.9012 yes 100.00%
dd-ls4 -64.8997 -64.9021 yes 100.00%
fgmd -64.8997 -inf yes 100.00%
fm-bca -64.8997 -64.8997 yes 100.00%
fm -64.8997 -78.7854 yes 100.00%
fw 0 -inf no 0.00%
ga -64.8997 -inf yes 100.00%
hbp -64.8997 -65.3005 yes 100.00%
ipfps -64.8997 -inf yes 100.00%
ipfpu -64.8997 -inf yes 100.00%
lsm -61.7124 -inf no 93.33%
mp -64.8997 -64.8997 yes 100.00%
mp-fw -64.8997 -64.8997 yes 100.00%
mpm -60.3249 -inf no 90.00%
mp-mcf -64.8997 -64.8997 yes 100.00%
pm -52.1421 -inf no 80.00%
rrwm -64.8997 -inf yes 100.00%
sm -64.8997 -inf yes 100.00%
smac -64.8997 -inf yes 100.00%

Run time 100s

method value bound optimal accuracy
dd-ls0 -64.8997 -64.9035 yes 100.00%
dd-ls3 -64.8997 -64.9012 yes 100.00%
dd-ls4 -64.8997 -64.9015 yes 100.00%
fgmd -64.8997 -inf yes 100.00%
fm-bca -64.8997 -64.8997 yes 100.00%
fm -64.8997 -78.7854 yes 100.00%
fw 0 -inf no 0.00%
ga -64.8997 -inf yes 100.00%
hbp -64.8997 -65.3005 yes 100.00%
ipfps -64.8997 -inf yes 100.00%
ipfpu -64.8997 -inf yes 100.00%
lsm -61.7124 -inf no 93.33%
mp -64.8997 -64.8997 yes 100.00%
mp-fw -64.8997 -64.8997 yes 100.00%
mpm -60.3249 -inf no 90.00%
mp-mcf -64.8997 -64.8997 yes 100.00%
pm -52.1421 -inf no 80.00%
rrwm -64.8997 -inf yes 100.00%
sm -64.8997 -inf yes 100.00%
smac -64.8997 -inf yes 100.00%

Run time 300s

method value bound optimal accuracy
dd-ls0 -64.8997 -64.9035 yes 100.00%
dd-ls3 -64.8997 -64.9012 yes 100.00%
dd-ls4 -64.8997 -64.9015 yes 100.00%
fgmd -64.8997 -inf yes 100.00%
fm-bca -64.8997 -64.8997 yes 100.00%
fm -64.8997 -78.7854 yes 100.00%
fw 0 -inf no 0.00%
ga -64.8997 -inf yes 100.00%
hbp -64.8997 -65.3005 yes 100.00%
ipfps -64.8997 -inf yes 100.00%
ipfpu -64.8997 -inf yes 100.00%
lsm -61.7124 -inf no 93.33%
mp -64.8997 -64.8997 yes 100.00%
mp-fw -64.8997 -64.8997 yes 100.00%
mpm -60.3249 -inf no 90.00%
mp-mcf -64.8997 -64.8997 yes 100.00%
pm -52.1421 -inf no 80.00%
rrwm -64.8997 -inf yes 100.00%
sm -64.8997 -inf yes 100.00%
smac -64.8997 -inf yes 100.00%

Other Results for this Dataset

Accumulated results for whole dataset: house-sparse

Results for individual instances of the dataset: