A Comparative Study of Graph Matching Algorithms in Computer Vision

Benchmark Results for “house-sparse18”

This page shows the benchmarks results for the dataset instance “house-sparse18”. We consider solutions as optimal if the objective value is within a 0.1% range of the known optimum -64.7595.

Run time 1s

method value bound optimal accuracy
dd-ls0 -64.7595 -64.7714 yes 100.00%
dd-ls3 -60.2755 -66.6266 no 93.33%
dd-ls4 -44.6536 -70.9694 no 73.33%
fgmd inf -inf no
fm-bca -64.7595 -64.7595 yes 100.00%
fm -64.7595 -78.7572 yes 100.00%
fw 0 -inf no 0.00%
ga -64.7595 -inf yes 100.00%
hbp -64.7595 -65.155 yes 100.00%
ipfps -64.7595 -inf yes 100.00%
ipfpu -64.7595 -inf yes 100.00%
lsm -61.5609 -inf no 93.33%
mp -64.7595 -64.7595 yes 100.00%
mp-fw -64.7595 -64.7595 yes 100.00%
mpm -60.2639 -inf no 90.00%
mp-mcf -64.7595 -64.7595 yes 100.00%
pm -52.0897 -inf no 80.00%
rrwm -64.7595 -inf yes 100.00%
sm -64.7595 -inf yes 100.00%
smac -11.6124 -inf no 0.00%

Run time 10s

method value bound optimal accuracy
dd-ls0 -64.7595 -64.7714 yes 100.00%
dd-ls3 -64.7595 -64.765 yes 100.00%
dd-ls4 -64.7595 -64.7688 yes 100.00%
fgmd -64.7595 -inf yes 100.00%
fm-bca -64.7595 -64.7595 yes 100.00%
fm -64.7595 -78.7572 yes 100.00%
fw 0 -inf no 0.00%
ga -64.7595 -inf yes 100.00%
hbp -64.7595 -65.155 yes 100.00%
ipfps -64.7595 -inf yes 100.00%
ipfpu -64.7595 -inf yes 100.00%
lsm -61.5609 -inf no 93.33%
mp -64.7595 -64.7595 yes 100.00%
mp-fw -64.7595 -64.7595 yes 100.00%
mpm -60.2639 -inf no 90.00%
mp-mcf -64.7595 -64.7595 yes 100.00%
pm -52.0897 -inf no 80.00%
rrwm -64.7595 -inf yes 100.00%
sm -64.7595 -inf yes 100.00%
smac -11.6124 -inf no 0.00%

Run time 100s

method value bound optimal accuracy
dd-ls0 -64.7595 -64.7714 yes 100.00%
dd-ls3 -64.7595 -64.765 yes 100.00%
dd-ls4 -64.7595 -64.7688 yes 100.00%
fgmd -64.7595 -inf yes 100.00%
fm-bca -64.7595 -64.7595 yes 100.00%
fm -64.7595 -78.7572 yes 100.00%
fw 0 -inf no 0.00%
ga -64.7595 -inf yes 100.00%
hbp -64.7595 -65.155 yes 100.00%
ipfps -64.7595 -inf yes 100.00%
ipfpu -64.7595 -inf yes 100.00%
lsm -61.5609 -inf no 93.33%
mp -64.7595 -64.7595 yes 100.00%
mp-fw -64.7595 -64.7595 yes 100.00%
mpm -60.2639 -inf no 90.00%
mp-mcf -64.7595 -64.7595 yes 100.00%
pm -52.0897 -inf no 80.00%
rrwm -64.7595 -inf yes 100.00%
sm -64.7595 -inf yes 100.00%
smac -11.6124 -inf no 0.00%

Run time 300s

method value bound optimal accuracy
dd-ls0 -64.7595 -64.7714 yes 100.00%
dd-ls3 -64.7595 -64.765 yes 100.00%
dd-ls4 -64.7595 -64.7688 yes 100.00%
fgmd -64.7595 -inf yes 100.00%
fm-bca -64.7595 -64.7595 yes 100.00%
fm -64.7595 -78.7572 yes 100.00%
fw 0 -inf no 0.00%
ga -64.7595 -inf yes 100.00%
hbp -64.7595 -65.155 yes 100.00%
ipfps -64.7595 -inf yes 100.00%
ipfpu -64.7595 -inf yes 100.00%
lsm -61.5609 -inf no 93.33%
mp -64.7595 -64.7595 yes 100.00%
mp-fw -64.7595 -64.7595 yes 100.00%
mpm -60.2639 -inf no 90.00%
mp-mcf -64.7595 -64.7595 yes 100.00%
pm -52.0897 -inf no 80.00%
rrwm -64.7595 -inf yes 100.00%
sm -64.7595 -inf yes 100.00%
smac -11.6124 -inf no 0.00%

Other Results for this Dataset

Accumulated results for whole dataset: house-sparse

Results for individual instances of the dataset: