A Comparative Study of Graph Matching Algorithms in Computer Vision

Benchmark Results for “house-sparse5”

This page shows the benchmarks results for the dataset instance “house-sparse5”. We consider solutions as optimal if the objective value is within a 0.1% range of the known optimum -64.9713.

Run time 1s

method value bound optimal accuracy
dd-ls0 -64.9713 -64.9715 yes 100.00%
dd-ls3 -64.9713 -64.9808 yes 100.00%
dd-ls4 -48.6453 -70.9617 no 76.67%
fgmd inf -inf no
fm-bca -64.9713 -64.9713 yes 100.00%
fm -64.9713 -78.8055 yes 100.00%
fw 0 -inf no 0.00%
ga -64.9713 -inf yes 100.00%
hbp -64.9713 -65.4054 yes 100.00%
ipfps -64.9713 -inf yes 100.00%
ipfpu -64.9713 -inf yes 100.00%
lsm -61.7794 -inf no 93.33%
mp -64.9713 -64.9713 yes 100.00%
mp-fw -64.9713 -64.9713 yes 100.00%
mpm -56.6246 -inf no 86.67%
mp-mcf -64.9713 -64.9713 yes 100.00%
pm -52.2744 -inf no 80.00%
rrwm -64.9713 -inf yes 100.00%
sm -64.9713 -inf yes 100.00%
smac -10.845 -inf no 0.00%

Run time 10s

method value bound optimal accuracy
dd-ls0 -64.9713 -64.9715 yes 100.00%
dd-ls3 -64.9713 -64.9808 yes 100.00%
dd-ls4 -64.9713 -64.98 yes 100.00%
fgmd -64.9713 -inf yes 100.00%
fm-bca -64.9713 -64.9713 yes 100.00%
fm -64.9713 -78.8055 yes 100.00%
fw 0 -inf no 0.00%
ga -64.9713 -inf yes 100.00%
hbp -64.9713 -65.4054 yes 100.00%
ipfps -64.9713 -inf yes 100.00%
ipfpu -64.9713 -inf yes 100.00%
lsm -61.7794 -inf no 93.33%
mp -64.9713 -64.9713 yes 100.00%
mp-fw -64.9713 -64.9713 yes 100.00%
mpm -56.6246 -inf no 86.67%
mp-mcf -64.9713 -64.9713 yes 100.00%
pm -52.2744 -inf no 80.00%
rrwm -64.9713 -inf yes 100.00%
sm -64.9713 -inf yes 100.00%
smac -10.845 -inf no 0.00%

Run time 100s

method value bound optimal accuracy
dd-ls0 -64.9713 -64.9715 yes 100.00%
dd-ls3 -64.9713 -64.9808 yes 100.00%
dd-ls4 -64.9713 -64.98 yes 100.00%
fgmd -64.9713 -inf yes 100.00%
fm-bca -64.9713 -64.9713 yes 100.00%
fm -64.9713 -78.8055 yes 100.00%
fw 0 -inf no 0.00%
ga -64.9713 -inf yes 100.00%
hbp -64.9713 -65.4054 yes 100.00%
ipfps -64.9713 -inf yes 100.00%
ipfpu -64.9713 -inf yes 100.00%
lsm -61.7794 -inf no 93.33%
mp -64.9713 -64.9713 yes 100.00%
mp-fw -64.9713 -64.9713 yes 100.00%
mpm -56.6246 -inf no 86.67%
mp-mcf -64.9713 -64.9713 yes 100.00%
pm -52.2744 -inf no 80.00%
rrwm -64.9713 -inf yes 100.00%
sm -64.9713 -inf yes 100.00%
smac -10.845 -inf no 0.00%

Run time 300s

method value bound optimal accuracy
dd-ls0 -64.9713 -64.9715 yes 100.00%
dd-ls3 -64.9713 -64.9808 yes 100.00%
dd-ls4 -64.9713 -64.98 yes 100.00%
fgmd -64.9713 -inf yes 100.00%
fm-bca -64.9713 -64.9713 yes 100.00%
fm -64.9713 -78.8055 yes 100.00%
fw 0 -inf no 0.00%
ga -64.9713 -inf yes 100.00%
hbp -64.9713 -65.4054 yes 100.00%
ipfps -64.9713 -inf yes 100.00%
ipfpu -64.9713 -inf yes 100.00%
lsm -61.7794 -inf no 93.33%
mp -64.9713 -64.9713 yes 100.00%
mp-fw -64.9713 -64.9713 yes 100.00%
mpm -56.6246 -inf no 86.67%
mp-mcf -64.9713 -64.9713 yes 100.00%
pm -52.2744 -inf no 80.00%
rrwm -64.9713 -inf yes 100.00%
sm -64.9713 -inf yes 100.00%
smac -10.845 -inf no 0.00%

Other Results for this Dataset

Accumulated results for whole dataset: house-sparse

Results for individual instances of the dataset: