A Comparative Study of Graph Matching Algorithms in Computer Vision

Benchmark Results for “house-sparse16”

This page shows the benchmarks results for the dataset instance “house-sparse16”. We consider solutions as optimal if the objective value is within a 0.1% range of the known optimum -66.1275.

Run time 1s

method value bound optimal accuracy
dd-ls0 -66.1275 -66.1298 yes 100.00%
dd-ls3 -66.1275 -66.1287 yes 100.00%
dd-ls4 -45.8043 -71.3619 no 73.33%
fgmd inf -inf no
fm-bca -66.1275 -66.1275 yes 100.00%
fm -66.1275 -78.8155 yes 100.00%
fw 0 -inf no 0.00%
ga -66.1275 -inf yes 100.00%
hbp -66.1275 -66.4427 yes 100.00%
ipfps -66.1275 -inf yes 100.00%
ipfpu -66.1275 -inf yes 100.00%
lsm -62.9101 -inf no 93.33%
mp -66.1275 -66.1275 yes 100.00%
mp-fw -66.1275 -66.1275 yes 100.00%
mpm -61.5494 -inf no 90.00%
mp-mcf -66.1275 -66.1275 yes 100.00%
pm -53.384 -inf no 80.00%
rrwm -66.1275 -inf yes 100.00%
sm -66.1275 -inf yes 100.00%
smac -11.4442 -inf no 0.00%

Run time 10s

method value bound optimal accuracy
dd-ls0 -66.1275 -66.1298 yes 100.00%
dd-ls3 -66.1275 -66.1287 yes 100.00%
dd-ls4 -66.1275 -66.128 yes 100.00%
fgmd -66.1275 -inf yes 100.00%
fm-bca -66.1275 -66.1275 yes 100.00%
fm -66.1275 -78.8155 yes 100.00%
fw 0 -inf no 0.00%
ga -66.1275 -inf yes 100.00%
hbp -66.1275 -66.4427 yes 100.00%
ipfps -66.1275 -inf yes 100.00%
ipfpu -66.1275 -inf yes 100.00%
lsm -62.9101 -inf no 93.33%
mp -66.1275 -66.1275 yes 100.00%
mp-fw -66.1275 -66.1275 yes 100.00%
mpm -61.5494 -inf no 90.00%
mp-mcf -66.1275 -66.1275 yes 100.00%
pm -53.384 -inf no 80.00%
rrwm -66.1275 -inf yes 100.00%
sm -66.1275 -inf yes 100.00%
smac -11.4442 -inf no 0.00%

Run time 100s

method value bound optimal accuracy
dd-ls0 -66.1275 -66.1298 yes 100.00%
dd-ls3 -66.1275 -66.1287 yes 100.00%
dd-ls4 -66.1275 -66.128 yes 100.00%
fgmd -66.1275 -inf yes 100.00%
fm-bca -66.1275 -66.1275 yes 100.00%
fm -66.1275 -78.8155 yes 100.00%
fw 0 -inf no 0.00%
ga -66.1275 -inf yes 100.00%
hbp -66.1275 -66.4427 yes 100.00%
ipfps -66.1275 -inf yes 100.00%
ipfpu -66.1275 -inf yes 100.00%
lsm -62.9101 -inf no 93.33%
mp -66.1275 -66.1275 yes 100.00%
mp-fw -66.1275 -66.1275 yes 100.00%
mpm -61.5494 -inf no 90.00%
mp-mcf -66.1275 -66.1275 yes 100.00%
pm -53.384 -inf no 80.00%
rrwm -66.1275 -inf yes 100.00%
sm -66.1275 -inf yes 100.00%
smac -11.4442 -inf no 0.00%

Run time 300s

method value bound optimal accuracy
dd-ls0 -66.1275 -66.1298 yes 100.00%
dd-ls3 -66.1275 -66.1287 yes 100.00%
dd-ls4 -66.1275 -66.128 yes 100.00%
fgmd -66.1275 -inf yes 100.00%
fm-bca -66.1275 -66.1275 yes 100.00%
fm -66.1275 -78.8155 yes 100.00%
fw 0 -inf no 0.00%
ga -66.1275 -inf yes 100.00%
hbp -66.1275 -66.4427 yes 100.00%
ipfps -66.1275 -inf yes 100.00%
ipfpu -66.1275 -inf yes 100.00%
lsm -62.9101 -inf no 93.33%
mp -66.1275 -66.1275 yes 100.00%
mp-fw -66.1275 -66.1275 yes 100.00%
mpm -61.5494 -inf no 90.00%
mp-mcf -66.1275 -66.1275 yes 100.00%
pm -53.384 -inf no 80.00%
rrwm -66.1275 -inf yes 100.00%
sm -66.1275 -inf yes 100.00%
smac -11.4442 -inf no 0.00%

Other Results for this Dataset

Accumulated results for whole dataset: house-sparse

Results for individual instances of the dataset: