A Comparative Study of Graph Matching Algorithms in Computer Vision

Benchmark Results for “house-sparse99”

This page shows the benchmarks results for the dataset instance “house-sparse99”. We consider solutions as optimal if the objective value is within a 0.1% range of the known optimum -67.4858.

Run time 1s

method value bound optimal accuracy
dd-ls0 -67.4858 -67.5276 yes 100.00%
dd-ls3 -67.4858 -67.4901 yes 100.00%
dd-ls4 -58.3588 -70.9393 no 90.00%
fgmd inf -inf no
fm-bca -67.4858 -67.4858 yes 100.00%
fm -67.4858 -78.8585 yes 100.00%
fw 0 -inf no 0.00%
ga -67.4858 -inf yes 100.00%
hbp -67.4858 -67.4858 yes 100.00%
ipfps -67.4858 -inf yes 100.00%
ipfpu -67.4858 -inf yes 100.00%
lsm -67.4858 -inf yes 100.00%
mp -67.4858 -67.4858 yes 100.00%
mp-fw -67.4858 -67.4858 yes 100.00%
mpm -59.2232 -inf no 93.33%
mp-mcf -67.4858 -67.4858 yes 100.00%
pm -56.6268 -inf no 86.67%
rrwm -67.4858 -inf yes 100.00%
sm -67.4858 -inf yes 100.00%
smac -47.3515 -inf no 73.33%

Run time 10s

method value bound optimal accuracy
dd-ls0 -67.4858 -67.5276 yes 100.00%
dd-ls3 -67.4858 -67.4901 yes 100.00%
dd-ls4 -67.4858 -67.4952 yes 100.00%
fgmd -67.4858 -inf yes 100.00%
fm-bca -67.4858 -67.4858 yes 100.00%
fm -67.4858 -78.8585 yes 100.00%
fw 0 -inf no 0.00%
ga -67.4858 -inf yes 100.00%
hbp -67.4858 -67.4858 yes 100.00%
ipfps -67.4858 -inf yes 100.00%
ipfpu -67.4858 -inf yes 100.00%
lsm -67.4858 -inf yes 100.00%
mp -67.4858 -67.4858 yes 100.00%
mp-fw -67.4858 -67.4858 yes 100.00%
mpm -59.2232 -inf no 93.33%
mp-mcf -67.4858 -67.4858 yes 100.00%
pm -56.6268 -inf no 86.67%
rrwm -67.4858 -inf yes 100.00%
sm -67.4858 -inf yes 100.00%
smac -47.3515 -inf no 73.33%

Run time 100s

method value bound optimal accuracy
dd-ls0 -67.4858 -67.5276 yes 100.00%
dd-ls3 -67.4858 -67.4901 yes 100.00%
dd-ls4 -67.4858 -67.4952 yes 100.00%
fgmd -67.4858 -inf yes 100.00%
fm-bca -67.4858 -67.4858 yes 100.00%
fm -67.4858 -78.8585 yes 100.00%
fw 0 -inf no 0.00%
ga -67.4858 -inf yes 100.00%
hbp -67.4858 -67.4858 yes 100.00%
ipfps -67.4858 -inf yes 100.00%
ipfpu -67.4858 -inf yes 100.00%
lsm -67.4858 -inf yes 100.00%
mp -67.4858 -67.4858 yes 100.00%
mp-fw -67.4858 -67.4858 yes 100.00%
mpm -59.2232 -inf no 93.33%
mp-mcf -67.4858 -67.4858 yes 100.00%
pm -56.6268 -inf no 86.67%
rrwm -67.4858 -inf yes 100.00%
sm -67.4858 -inf yes 100.00%
smac -47.3515 -inf no 73.33%

Run time 300s

method value bound optimal accuracy
dd-ls0 -67.4858 -67.5276 yes 100.00%
dd-ls3 -67.4858 -67.4901 yes 100.00%
dd-ls4 -67.4858 -67.4952 yes 100.00%
fgmd -67.4858 -inf yes 100.00%
fm-bca -67.4858 -67.4858 yes 100.00%
fm -67.4858 -78.8585 yes 100.00%
fw 0 -inf no 0.00%
ga -67.4858 -inf yes 100.00%
hbp -67.4858 -67.4858 yes 100.00%
ipfps -67.4858 -inf yes 100.00%
ipfpu -67.4858 -inf yes 100.00%
lsm -67.4858 -inf yes 100.00%
mp -67.4858 -67.4858 yes 100.00%
mp-fw -67.4858 -67.4858 yes 100.00%
mpm -59.2232 -inf no 93.33%
mp-mcf -67.4858 -67.4858 yes 100.00%
pm -56.6268 -inf no 86.67%
rrwm -67.4858 -inf yes 100.00%
sm -67.4858 -inf yes 100.00%
smac -47.3515 -inf no 73.33%

Other Results for this Dataset

Accumulated results for whole dataset: house-sparse

Results for individual instances of the dataset: