A Comparative Study of Graph Matching Algorithms in Computer Vision

Benchmark Results for “house-sparse39”

This page shows the benchmarks results for the dataset instance “house-sparse39”. We consider solutions as optimal if the objective value is within a 0.1% range of the known optimum -67.0283.

Run time 1s

method value bound optimal accuracy
dd-ls0 -67.0283 -67.029 yes 100.00%
dd-ls3 -67.0283 -67.0364 yes 100.00%
dd-ls4 -67.0283 -71.6791 yes 100.00%
fgmd inf -inf no
fm-bca -67.0283 -67.0283 yes 100.00%
fm -67.0283 -78.8662 yes 100.00%
fw 0 -inf no 0.00%
ga -67.0283 -inf yes 100.00%
hbp -67.0283 -67.0761 yes 100.00%
ipfps -67.0283 -inf yes 100.00%
ipfpu -67.0283 -inf yes 100.00%
lsm -67.0283 -inf yes 100.00%
mp -67.0283 -67.0283 yes 100.00%
mp-fw -67.0283 -67.0283 yes 100.00%
mpm -62.4008 -inf no 90.00%
mp-mcf -67.0283 -67.0283 yes 100.00%
pm -56.147 -inf no 86.67%
rrwm -67.0283 -inf yes 100.00%
sm -67.0283 -inf yes 100.00%
smac -7.31466 -inf no 0.00%

Run time 10s

method value bound optimal accuracy
dd-ls0 -67.0283 -67.029 yes 100.00%
dd-ls3 -67.0283 -67.0364 yes 100.00%
dd-ls4 -67.0283 -67.03 yes 100.00%
fgmd -67.0283 -inf yes 100.00%
fm-bca -67.0283 -67.0283 yes 100.00%
fm -67.0283 -78.8662 yes 100.00%
fw 0 -inf no 0.00%
ga -67.0283 -inf yes 100.00%
hbp -67.0283 -67.0761 yes 100.00%
ipfps -67.0283 -inf yes 100.00%
ipfpu -67.0283 -inf yes 100.00%
lsm -67.0283 -inf yes 100.00%
mp -67.0283 -67.0283 yes 100.00%
mp-fw -67.0283 -67.0283 yes 100.00%
mpm -62.4008 -inf no 90.00%
mp-mcf -67.0283 -67.0283 yes 100.00%
pm -56.147 -inf no 86.67%
rrwm -67.0283 -inf yes 100.00%
sm -67.0283 -inf yes 100.00%
smac -7.31466 -inf no 0.00%

Run time 100s

method value bound optimal accuracy
dd-ls0 -67.0283 -67.029 yes 100.00%
dd-ls3 -67.0283 -67.0364 yes 100.00%
dd-ls4 -67.0283 -67.03 yes 100.00%
fgmd -67.0283 -inf yes 100.00%
fm-bca -67.0283 -67.0283 yes 100.00%
fm -67.0283 -78.8662 yes 100.00%
fw 0 -inf no 0.00%
ga -67.0283 -inf yes 100.00%
hbp -67.0283 -67.0761 yes 100.00%
ipfps -67.0283 -inf yes 100.00%
ipfpu -67.0283 -inf yes 100.00%
lsm -67.0283 -inf yes 100.00%
mp -67.0283 -67.0283 yes 100.00%
mp-fw -67.0283 -67.0283 yes 100.00%
mpm -62.4008 -inf no 90.00%
mp-mcf -67.0283 -67.0283 yes 100.00%
pm -56.147 -inf no 86.67%
rrwm -67.0283 -inf yes 100.00%
sm -67.0283 -inf yes 100.00%
smac -7.31466 -inf no 0.00%

Run time 300s

method value bound optimal accuracy
dd-ls0 -67.0283 -67.029 yes 100.00%
dd-ls3 -67.0283 -67.0364 yes 100.00%
dd-ls4 -67.0283 -67.03 yes 100.00%
fgmd -67.0283 -inf yes 100.00%
fm-bca -67.0283 -67.0283 yes 100.00%
fm -67.0283 -78.8662 yes 100.00%
fw 0 -inf no 0.00%
ga -67.0283 -inf yes 100.00%
hbp -67.0283 -67.0761 yes 100.00%
ipfps -67.0283 -inf yes 100.00%
ipfpu -67.0283 -inf yes 100.00%
lsm -67.0283 -inf yes 100.00%
mp -67.0283 -67.0283 yes 100.00%
mp-fw -67.0283 -67.0283 yes 100.00%
mpm -62.4008 -inf no 90.00%
mp-mcf -67.0283 -67.0283 yes 100.00%
pm -56.147 -inf no 86.67%
rrwm -67.0283 -inf yes 100.00%
sm -67.0283 -inf yes 100.00%
smac -7.31466 -inf no 0.00%

Other Results for this Dataset

Accumulated results for whole dataset: house-sparse

Results for individual instances of the dataset: