A Comparative Study of Graph Matching Algorithms in Computer Vision

Benchmark Results for “house-sparse24”

This page shows the benchmarks results for the dataset instance “house-sparse24”. We consider solutions as optimal if the objective value is within a 0.1% range of the known optimum -66.7875.

Run time 1s

method value bound optimal accuracy
dd-ls0 -66.7875 -66.7911 yes 100.00%
dd-ls3 -66.7875 -66.808 yes 100.00%
dd-ls4 -52.4991 -73.1121 no 80.00%
fgmd inf -inf no
fm-bca -66.7875 -66.7875 yes 100.00%
fm -66.7875 -78.8521 yes 100.00%
fw 0 -inf no 0.00%
ga -66.7875 -inf yes 100.00%
hbp -66.7875 -66.8633 yes 100.00%
ipfps -66.7875 -inf yes 100.00%
ipfpu -66.7875 -inf yes 100.00%
lsm -66.7875 -inf yes 100.00%
mp -66.7875 -66.7875 yes 100.00%
mp-fw -66.7875 -66.7875 yes 100.00%
mpm -62.2381 -inf no 90.00%
mp-mcf -66.7875 -66.7875 yes 100.00%
pm -55.8589 -inf no 86.67%
rrwm -66.7875 -inf yes 100.00%
sm -66.7875 -inf yes 100.00%
smac -10.6139 -inf no 0.00%

Run time 10s

method value bound optimal accuracy
dd-ls0 -66.7875 -66.7911 yes 100.00%
dd-ls3 -66.7875 -66.808 yes 100.00%
dd-ls4 -66.7875 -66.7882 yes 100.00%
fgmd -66.7875 -inf yes 100.00%
fm-bca -66.7875 -66.7875 yes 100.00%
fm -66.7875 -78.8521 yes 100.00%
fw 0 -inf no 0.00%
ga -66.7875 -inf yes 100.00%
hbp -66.7875 -66.8633 yes 100.00%
ipfps -66.7875 -inf yes 100.00%
ipfpu -66.7875 -inf yes 100.00%
lsm -66.7875 -inf yes 100.00%
mp -66.7875 -66.7875 yes 100.00%
mp-fw -66.7875 -66.7875 yes 100.00%
mpm -62.2381 -inf no 90.00%
mp-mcf -66.7875 -66.7875 yes 100.00%
pm -55.8589 -inf no 86.67%
rrwm -66.7875 -inf yes 100.00%
sm -66.7875 -inf yes 100.00%
smac -10.6139 -inf no 0.00%

Run time 100s

method value bound optimal accuracy
dd-ls0 -66.7875 -66.7911 yes 100.00%
dd-ls3 -66.7875 -66.808 yes 100.00%
dd-ls4 -66.7875 -66.7882 yes 100.00%
fgmd -66.7875 -inf yes 100.00%
fm-bca -66.7875 -66.7875 yes 100.00%
fm -66.7875 -78.8521 yes 100.00%
fw 0 -inf no 0.00%
ga -66.7875 -inf yes 100.00%
hbp -66.7875 -66.8633 yes 100.00%
ipfps -66.7875 -inf yes 100.00%
ipfpu -66.7875 -inf yes 100.00%
lsm -66.7875 -inf yes 100.00%
mp -66.7875 -66.7875 yes 100.00%
mp-fw -66.7875 -66.7875 yes 100.00%
mpm -62.2381 -inf no 90.00%
mp-mcf -66.7875 -66.7875 yes 100.00%
pm -55.8589 -inf no 86.67%
rrwm -66.7875 -inf yes 100.00%
sm -66.7875 -inf yes 100.00%
smac -10.6139 -inf no 0.00%

Run time 300s

method value bound optimal accuracy
dd-ls0 -66.7875 -66.7911 yes 100.00%
dd-ls3 -66.7875 -66.808 yes 100.00%
dd-ls4 -66.7875 -66.7882 yes 100.00%
fgmd -66.7875 -inf yes 100.00%
fm-bca -66.7875 -66.7875 yes 100.00%
fm -66.7875 -78.8521 yes 100.00%
fw 0 -inf no 0.00%
ga -66.7875 -inf yes 100.00%
hbp -66.7875 -66.8633 yes 100.00%
ipfps -66.7875 -inf yes 100.00%
ipfpu -66.7875 -inf yes 100.00%
lsm -66.7875 -inf yes 100.00%
mp -66.7875 -66.7875 yes 100.00%
mp-fw -66.7875 -66.7875 yes 100.00%
mpm -62.2381 -inf no 90.00%
mp-mcf -66.7875 -66.7875 yes 100.00%
pm -55.8589 -inf no 86.67%
rrwm -66.7875 -inf yes 100.00%
sm -66.7875 -inf yes 100.00%
smac -10.6139 -inf no 0.00%

Other Results for this Dataset

Accumulated results for whole dataset: house-sparse

Results for individual instances of the dataset: