A Comparative Study of Graph Matching Algorithms in Computer Vision

Benchmark Results for “house-sparse69”

This page shows the benchmarks results for the dataset instance “house-sparse69”. We consider solutions as optimal if the objective value is within a 0.1% range of the known optimum -67.3002.

Run time 1s

method value bound optimal accuracy
dd-ls0 -67.3002 -67.3158 yes 100.00%
dd-ls3 -67.3002 -67.3035 yes 100.00%
dd-ls4 -63.1236 -72.1502 no 96.67%
fgmd inf -inf no
fm-bca -67.3002 -67.3002 yes 100.00%
fm -67.3002 -78.8319 yes 100.00%
fw 0 -inf no 0.00%
ga -67.3002 -inf yes 100.00%
hbp -67.3002 -67.6526 yes 100.00%
ipfps -67.3002 -inf yes 100.00%
ipfpu -67.3002 -inf yes 100.00%
lsm -64.0948 -inf no 93.33%
mp -67.3002 -67.3002 yes 100.00%
mp-fw -67.3002 -67.3002 yes 100.00%
mpm -62.5279 -inf no 90.00%
mp-mcf -67.3002 -67.3002 yes 100.00%
pm -53.3587 -inf no 80.00%
rrwm -67.3002 -inf yes 100.00%
sm -67.3002 -inf yes 100.00%
smac -41.2782 -inf no 66.67%

Run time 10s

method value bound optimal accuracy
dd-ls0 -67.3002 -67.3158 yes 100.00%
dd-ls3 -67.3002 -67.3035 yes 100.00%
dd-ls4 -67.3002 -67.3089 yes 100.00%
fgmd -67.3002 -inf yes 100.00%
fm-bca -67.3002 -67.3002 yes 100.00%
fm -67.3002 -78.8319 yes 100.00%
fw 0 -inf no 0.00%
ga -67.3002 -inf yes 100.00%
hbp -67.3002 -67.6526 yes 100.00%
ipfps -67.3002 -inf yes 100.00%
ipfpu -67.3002 -inf yes 100.00%
lsm -64.0948 -inf no 93.33%
mp -67.3002 -67.3002 yes 100.00%
mp-fw -67.3002 -67.3002 yes 100.00%
mpm -62.5279 -inf no 90.00%
mp-mcf -67.3002 -67.3002 yes 100.00%
pm -53.3587 -inf no 80.00%
rrwm -67.3002 -inf yes 100.00%
sm -67.3002 -inf yes 100.00%
smac -41.2782 -inf no 66.67%

Run time 100s

method value bound optimal accuracy
dd-ls0 -67.3002 -67.3158 yes 100.00%
dd-ls3 -67.3002 -67.3035 yes 100.00%
dd-ls4 -67.3002 -67.3089 yes 100.00%
fgmd -67.3002 -inf yes 100.00%
fm-bca -67.3002 -67.3002 yes 100.00%
fm -67.3002 -78.8319 yes 100.00%
fw 0 -inf no 0.00%
ga -67.3002 -inf yes 100.00%
hbp -67.3002 -67.6526 yes 100.00%
ipfps -67.3002 -inf yes 100.00%
ipfpu -67.3002 -inf yes 100.00%
lsm -64.0948 -inf no 93.33%
mp -67.3002 -67.3002 yes 100.00%
mp-fw -67.3002 -67.3002 yes 100.00%
mpm -62.5279 -inf no 90.00%
mp-mcf -67.3002 -67.3002 yes 100.00%
pm -53.3587 -inf no 80.00%
rrwm -67.3002 -inf yes 100.00%
sm -67.3002 -inf yes 100.00%
smac -41.2782 -inf no 66.67%

Run time 300s

method value bound optimal accuracy
dd-ls0 -67.3002 -67.3158 yes 100.00%
dd-ls3 -67.3002 -67.3035 yes 100.00%
dd-ls4 -67.3002 -67.3089 yes 100.00%
fgmd -67.3002 -inf yes 100.00%
fm-bca -67.3002 -67.3002 yes 100.00%
fm -67.3002 -78.8319 yes 100.00%
fw 0 -inf no 0.00%
ga -67.3002 -inf yes 100.00%
hbp -67.3002 -67.6526 yes 100.00%
ipfps -67.3002 -inf yes 100.00%
ipfpu -67.3002 -inf yes 100.00%
lsm -64.0948 -inf no 93.33%
mp -67.3002 -67.3002 yes 100.00%
mp-fw -67.3002 -67.3002 yes 100.00%
mpm -62.5279 -inf no 90.00%
mp-mcf -67.3002 -67.3002 yes 100.00%
pm -53.3587 -inf no 80.00%
rrwm -67.3002 -inf yes 100.00%
sm -67.3002 -inf yes 100.00%
smac -41.2782 -inf no 66.67%

Other Results for this Dataset

Accumulated results for whole dataset: house-sparse

Results for individual instances of the dataset: