A Comparative Study of Graph Matching Algorithms in Computer Vision

Benchmark Results for “house-dense29”

This page shows the benchmarks results for the dataset instance “house-dense29”. We consider solutions as optimal if the objective value is within a 0.1% range of the known optimum -3765.23.

Run time 1s

method value bound optimal accuracy
dd-ls0 -3765.23 -3767.83 yes 100.00%
dd-ls3 -3765.23 -3765.58 yes 100.00%
dd-ls4 -3765.23 -3776.84 yes 100.00%
fgmd inf -inf no
fm-bca -3765.23 -3766.44 yes 100.00%
fm -3765.23 -4099.15 yes 100.00%
fw -3765.23 -inf yes 100.00%
ga 3387.48 -inf no 3.33%
hbp -3765.23 -3792.01 yes 100.00%
ipfps 3387.48 -inf no 3.33%
ipfpu 3387.48 -inf no 3.33%
lsm inf -inf no
mp -3765.23 -3765.23 yes 100.00%
mp-fw -3765.23 -3839.51 yes 100.00%
mpm 2017.34 -inf no 46.67%
mp-mcf -3387.81 -3819.2 no 80.00%
pm 3483.97 -inf no 16.67%
rrwm 3219.36 -inf no 3.33%
sm 4259.01 -inf no 6.67%
smac 2794.63 -inf no 30.00%

Run time 10s

method value bound optimal accuracy
dd-ls0 -3765.23 -3767.83 yes 100.00%
dd-ls3 -3765.23 -3765.58 yes 100.00%
dd-ls4 -3765.23 -3765.75 yes 100.00%
fgmd inf -inf no
fm-bca -3765.23 -3765.23 yes 100.00%
fm -3765.23 -4099.15 yes 100.00%
fw -3765.23 -inf yes 100.00%
ga 3387.48 -inf no 3.33%
hbp -3765.23 -3792.01 yes 100.00%
ipfps 3387.48 -inf no 3.33%
ipfpu 3387.48 -inf no 3.33%
lsm 2486.31 -inf no 20.00%
mp -3765.23 -3765.23 yes 100.00%
mp-fw -3765.23 -3791.53 yes 100.00%
mpm 2017.34 -inf no 46.67%
mp-mcf -3660.88 -3770.59 no 93.33%
pm 3483.97 -inf no 16.67%
rrwm 3219.36 -inf no 3.33%
sm 4259.01 -inf no 6.67%
smac 2794.63 -inf no 30.00%

Run time 100s

method value bound optimal accuracy
dd-ls0 -3765.23 -3767.83 yes 100.00%
dd-ls3 -3765.23 -3765.58 yes 100.00%
dd-ls4 -3765.23 -3765.75 yes 100.00%
fgmd -3765.23 -inf yes 100.00%
fm-bca -3765.23 -3765.23 yes 100.00%
fm -3765.23 -4099.15 yes 100.00%
fw -3765.23 -inf yes 100.00%
ga 3387.48 -inf no 3.33%
hbp -3765.23 -3792.01 yes 100.00%
ipfps 3387.48 -inf no 3.33%
ipfpu 3387.48 -inf no 3.33%
lsm 2486.31 -inf no 20.00%
mp -3765.23 -3765.23 yes 100.00%
mp-fw -3765.23 -3765.23 yes 100.00%
mpm 2017.34 -inf no 46.67%
mp-mcf -3765.23 -3765.23 yes 100.00%
pm 3483.97 -inf no 16.67%
rrwm 3219.36 -inf no 3.33%
sm 4259.01 -inf no 6.67%
smac 2794.63 -inf no 30.00%

Run time 300s

method value bound optimal accuracy
dd-ls0 -3765.23 -3767.83 yes 100.00%
dd-ls3 -3765.23 -3765.58 yes 100.00%
dd-ls4 -3765.23 -3765.75 yes 100.00%
fgmd -3765.23 -inf yes 100.00%
fm-bca -3765.23 -3765.23 yes 100.00%
fm -3765.23 -4099.15 yes 100.00%
fw -3765.23 -inf yes 100.00%
ga 3387.48 -inf no 3.33%
hbp -3765.23 -3792.01 yes 100.00%
ipfps 3387.48 -inf no 3.33%
ipfpu 3387.48 -inf no 3.33%
lsm 2486.31 -inf no 20.00%
mp -3765.23 -3765.23 yes 100.00%
mp-fw -3765.23 -3765.23 yes 100.00%
mpm 2017.34 -inf no 46.67%
mp-mcf -3765.23 -3765.23 yes 100.00%
pm 3483.97 -inf no 16.67%
rrwm 3219.36 -inf no 3.33%
sm 4259.01 -inf no 6.67%
smac 2794.63 -inf no 30.00%

Other Results for this Dataset

Accumulated results for whole dataset: house-dense

Results for individual instances of the dataset: