A Comparative Study of Graph Matching Algorithms in Computer Vision

Benchmark Results for “house-sparse12”

This page shows the benchmarks results for the dataset instance “house-sparse12”. We consider solutions as optimal if the objective value is within a 0.1% range of the known optimum -66.0209.

Run time 1s

method value bound optimal accuracy
dd-ls0 -66.0209 -66.0242 yes 100.00%
dd-ls3 -66.0209 -66.0624 yes 100.00%
dd-ls4 -49.7365 -72.7928 no 76.67%
fgmd inf -inf no
fm-bca -66.0209 -66.0209 yes 100.00%
fm -66.0209 -78.805 yes 100.00%
fw 0 -inf no 0.00%
ga -66.0209 -inf yes 100.00%
hbp -66.0209 -66.4109 yes 100.00%
ipfps -66.0209 -inf yes 100.00%
ipfpu -66.0209 -inf yes 100.00%
lsm -62.7974 -inf no 93.33%
mp -66.0209 -66.0209 yes 100.00%
mp-fw -66.0209 -66.0209 yes 100.00%
mpm -61.4049 -inf no 90.00%
mp-mcf -66.0209 -66.0209 yes 100.00%
pm -53.3795 -inf no 80.00%
rrwm -66.0209 -inf yes 100.00%
sm -66.0209 -inf yes 100.00%
smac -9.66516 -inf no 0.00%

Run time 10s

method value bound optimal accuracy
dd-ls0 -66.0209 -66.0242 yes 100.00%
dd-ls3 -66.0209 -66.0216 yes 100.00%
dd-ls4 -66.0209 -66.2303 yes 100.00%
fgmd -66.0209 -inf yes 100.00%
fm-bca -66.0209 -66.0209 yes 100.00%
fm -66.0209 -78.805 yes 100.00%
fw 0 -inf no 0.00%
ga -66.0209 -inf yes 100.00%
hbp -66.0209 -66.4109 yes 100.00%
ipfps -66.0209 -inf yes 100.00%
ipfpu -66.0209 -inf yes 100.00%
lsm -62.7974 -inf no 93.33%
mp -66.0209 -66.0209 yes 100.00%
mp-fw -66.0209 -66.0209 yes 100.00%
mpm -61.4049 -inf no 90.00%
mp-mcf -66.0209 -66.0209 yes 100.00%
pm -53.3795 -inf no 80.00%
rrwm -66.0209 -inf yes 100.00%
sm -66.0209 -inf yes 100.00%
smac -9.66516 -inf no 0.00%

Run time 100s

method value bound optimal accuracy
dd-ls0 -66.0209 -66.0242 yes 100.00%
dd-ls3 -66.0209 -66.0216 yes 100.00%
dd-ls4 -66.0209 -66.0223 yes 100.00%
fgmd -66.0209 -inf yes 100.00%
fm-bca -66.0209 -66.0209 yes 100.00%
fm -66.0209 -78.805 yes 100.00%
fw 0 -inf no 0.00%
ga -66.0209 -inf yes 100.00%
hbp -66.0209 -66.4109 yes 100.00%
ipfps -66.0209 -inf yes 100.00%
ipfpu -66.0209 -inf yes 100.00%
lsm -62.7974 -inf no 93.33%
mp -66.0209 -66.0209 yes 100.00%
mp-fw -66.0209 -66.0209 yes 100.00%
mpm -61.4049 -inf no 90.00%
mp-mcf -66.0209 -66.0209 yes 100.00%
pm -53.3795 -inf no 80.00%
rrwm -66.0209 -inf yes 100.00%
sm -66.0209 -inf yes 100.00%
smac -9.66516 -inf no 0.00%

Run time 300s

method value bound optimal accuracy
dd-ls0 -66.0209 -66.0242 yes 100.00%
dd-ls3 -66.0209 -66.0216 yes 100.00%
dd-ls4 -66.0209 -66.0223 yes 100.00%
fgmd -66.0209 -inf yes 100.00%
fm-bca -66.0209 -66.0209 yes 100.00%
fm -66.0209 -78.805 yes 100.00%
fw 0 -inf no 0.00%
ga -66.0209 -inf yes 100.00%
hbp -66.0209 -66.4109 yes 100.00%
ipfps -66.0209 -inf yes 100.00%
ipfpu -66.0209 -inf yes 100.00%
lsm -62.7974 -inf no 93.33%
mp -66.0209 -66.0209 yes 100.00%
mp-fw -66.0209 -66.0209 yes 100.00%
mpm -61.4049 -inf no 90.00%
mp-mcf -66.0209 -66.0209 yes 100.00%
pm -53.3795 -inf no 80.00%
rrwm -66.0209 -inf yes 100.00%
sm -66.0209 -inf yes 100.00%
smac -9.66516 -inf no 0.00%

Other Results for this Dataset

Accumulated results for whole dataset: house-sparse

Results for individual instances of the dataset: