A Comparative Study of Graph Matching Algorithms in Computer Vision

Benchmark Results for “house-sparse102”

This page shows the benchmarks results for the dataset instance “house-sparse102”. We consider solutions as optimal if the objective value is within a 0.1% range of the known optimum -68.5714.

Run time 1s

method value bound optimal accuracy
dd-ls0 -68.5714 -68.5763 yes 100.00%
dd-ls3 -68.5714 -68.5774 yes 100.00%
dd-ls4 -68.5714 -70.0435 yes 100.00%
fgmd inf -inf no
fm-bca -68.5714 -68.5714 yes 100.00%
fm -68.5714 -78.8204 yes 100.00%
fw 0 -inf no 0.00%
ga -68.5714 -inf yes 100.00%
hbp -68.5714 -68.5714 yes 100.00%
ipfps -68.5714 -inf yes 100.00%
ipfpu -68.5714 -inf yes 100.00%
lsm -68.5714 -inf yes 100.00%
mp -68.5714 -68.5714 yes 100.00%
mp-fw -68.5714 -68.5714 yes 100.00%
mpm -60.3225 -inf no 93.33%
mp-mcf -68.5714 -68.5714 yes 100.00%
pm -57.727 -inf no 86.67%
rrwm -68.5714 -inf yes 100.00%
sm -68.5714 -inf yes 100.00%
smac -47.3038 -inf no 73.33%

Run time 10s

method value bound optimal accuracy
dd-ls0 -68.5714 -68.5763 yes 100.00%
dd-ls3 -68.5714 -68.5774 yes 100.00%
dd-ls4 -68.5714 -68.5751 yes 100.00%
fgmd -68.5714 -inf yes 100.00%
fm-bca -68.5714 -68.5714 yes 100.00%
fm -68.5714 -78.8204 yes 100.00%
fw 0 -inf no 0.00%
ga -68.5714 -inf yes 100.00%
hbp -68.5714 -68.5714 yes 100.00%
ipfps -68.5714 -inf yes 100.00%
ipfpu -68.5714 -inf yes 100.00%
lsm -68.5714 -inf yes 100.00%
mp -68.5714 -68.5714 yes 100.00%
mp-fw -68.5714 -68.5714 yes 100.00%
mpm -60.3225 -inf no 93.33%
mp-mcf -68.5714 -68.5714 yes 100.00%
pm -57.727 -inf no 86.67%
rrwm -68.5714 -inf yes 100.00%
sm -68.5714 -inf yes 100.00%
smac -47.3038 -inf no 73.33%

Run time 100s

method value bound optimal accuracy
dd-ls0 -68.5714 -68.5763 yes 100.00%
dd-ls3 -68.5714 -68.5774 yes 100.00%
dd-ls4 -68.5714 -68.5751 yes 100.00%
fgmd -68.5714 -inf yes 100.00%
fm-bca -68.5714 -68.5714 yes 100.00%
fm -68.5714 -78.8204 yes 100.00%
fw 0 -inf no 0.00%
ga -68.5714 -inf yes 100.00%
hbp -68.5714 -68.5714 yes 100.00%
ipfps -68.5714 -inf yes 100.00%
ipfpu -68.5714 -inf yes 100.00%
lsm -68.5714 -inf yes 100.00%
mp -68.5714 -68.5714 yes 100.00%
mp-fw -68.5714 -68.5714 yes 100.00%
mpm -60.3225 -inf no 93.33%
mp-mcf -68.5714 -68.5714 yes 100.00%
pm -57.727 -inf no 86.67%
rrwm -68.5714 -inf yes 100.00%
sm -68.5714 -inf yes 100.00%
smac -47.3038 -inf no 73.33%

Run time 300s

method value bound optimal accuracy
dd-ls0 -68.5714 -68.5763 yes 100.00%
dd-ls3 -68.5714 -68.5774 yes 100.00%
dd-ls4 -68.5714 -68.5751 yes 100.00%
fgmd -68.5714 -inf yes 100.00%
fm-bca -68.5714 -68.5714 yes 100.00%
fm -68.5714 -78.8204 yes 100.00%
fw 0 -inf no 0.00%
ga -68.5714 -inf yes 100.00%
hbp -68.5714 -68.5714 yes 100.00%
ipfps -68.5714 -inf yes 100.00%
ipfpu -68.5714 -inf yes 100.00%
lsm -68.5714 -inf yes 100.00%
mp -68.5714 -68.5714 yes 100.00%
mp-fw -68.5714 -68.5714 yes 100.00%
mpm -60.3225 -inf no 93.33%
mp-mcf -68.5714 -68.5714 yes 100.00%
pm -57.727 -inf no 86.67%
rrwm -68.5714 -inf yes 100.00%
sm -68.5714 -inf yes 100.00%
smac -47.3038 -inf no 73.33%

Other Results for this Dataset

Accumulated results for whole dataset: house-sparse

Results for individual instances of the dataset: