A Comparative Study of Graph Matching Algorithms in Computer Vision

Benchmark Results for “house-sparse104”

This page shows the benchmarks results for the dataset instance “house-sparse104”. We consider solutions as optimal if the objective value is within a 0.1% range of the known optimum -68.5958.

Run time 1s

method value bound optimal accuracy
dd-ls0 -68.5958 -68.6644 yes 100.00%
dd-ls3 -68.5958 -68.6022 yes 100.00%
dd-ls4 -61.4186 -72.2127 no 93.33%
fgmd inf -inf no
fm-bca -68.5958 -68.5958 yes 100.00%
fm -68.5958 -78.8523 yes 100.00%
fw 0 -inf no 0.00%
ga -68.5958 -inf yes 100.00%
hbp -68.5958 -68.5958 yes 100.00%
ipfps -68.5958 -inf yes 100.00%
ipfpu -68.5958 -inf yes 100.00%
lsm -68.5958 -inf yes 100.00%
mp -68.5958 -68.5958 yes 100.00%
mp-fw -68.5958 -68.5958 yes 100.00%
mpm -60.3171 -inf no 93.33%
mp-mcf -68.5958 -68.5958 yes 100.00%
pm -59.4906 -inf no 90.00%
rrwm -68.5958 -inf yes 100.00%
sm -68.5958 -inf yes 100.00%
smac -51.5178 -inf no 83.33%

Run time 10s

method value bound optimal accuracy
dd-ls0 -68.5958 -68.6644 yes 100.00%
dd-ls3 -68.5958 -68.6022 yes 100.00%
dd-ls4 -68.5958 -68.6036 yes 100.00%
fgmd -68.5958 -inf yes 100.00%
fm-bca -68.5958 -68.5958 yes 100.00%
fm -68.5958 -78.8523 yes 100.00%
fw 0 -inf no 0.00%
ga -68.5958 -inf yes 100.00%
hbp -68.5958 -68.5958 yes 100.00%
ipfps -68.5958 -inf yes 100.00%
ipfpu -68.5958 -inf yes 100.00%
lsm -68.5958 -inf yes 100.00%
mp -68.5958 -68.5958 yes 100.00%
mp-fw -68.5958 -68.5958 yes 100.00%
mpm -60.3171 -inf no 93.33%
mp-mcf -68.5958 -68.5958 yes 100.00%
pm -59.4906 -inf no 90.00%
rrwm -68.5958 -inf yes 100.00%
sm -68.5958 -inf yes 100.00%
smac -51.5178 -inf no 83.33%

Run time 100s

method value bound optimal accuracy
dd-ls0 -68.5958 -68.6644 yes 100.00%
dd-ls3 -68.5958 -68.6022 yes 100.00%
dd-ls4 -68.5958 -68.6036 yes 100.00%
fgmd -68.5958 -inf yes 100.00%
fm-bca -68.5958 -68.5958 yes 100.00%
fm -68.5958 -78.8523 yes 100.00%
fw 0 -inf no 0.00%
ga -68.5958 -inf yes 100.00%
hbp -68.5958 -68.5958 yes 100.00%
ipfps -68.5958 -inf yes 100.00%
ipfpu -68.5958 -inf yes 100.00%
lsm -68.5958 -inf yes 100.00%
mp -68.5958 -68.5958 yes 100.00%
mp-fw -68.5958 -68.5958 yes 100.00%
mpm -60.3171 -inf no 93.33%
mp-mcf -68.5958 -68.5958 yes 100.00%
pm -59.4906 -inf no 90.00%
rrwm -68.5958 -inf yes 100.00%
sm -68.5958 -inf yes 100.00%
smac -51.5178 -inf no 83.33%

Run time 300s

method value bound optimal accuracy
dd-ls0 -68.5958 -68.6644 yes 100.00%
dd-ls3 -68.5958 -68.6022 yes 100.00%
dd-ls4 -68.5958 -68.6036 yes 100.00%
fgmd -68.5958 -inf yes 100.00%
fm-bca -68.5958 -68.5958 yes 100.00%
fm -68.5958 -78.8523 yes 100.00%
fw 0 -inf no 0.00%
ga -68.5958 -inf yes 100.00%
hbp -68.5958 -68.5958 yes 100.00%
ipfps -68.5958 -inf yes 100.00%
ipfpu -68.5958 -inf yes 100.00%
lsm -68.5958 -inf yes 100.00%
mp -68.5958 -68.5958 yes 100.00%
mp-fw -68.5958 -68.5958 yes 100.00%
mpm -60.3171 -inf no 93.33%
mp-mcf -68.5958 -68.5958 yes 100.00%
pm -59.4906 -inf no 90.00%
rrwm -68.5958 -inf yes 100.00%
sm -68.5958 -inf yes 100.00%
smac -51.5178 -inf no 83.33%

Other Results for this Dataset

Accumulated results for whole dataset: house-sparse

Results for individual instances of the dataset: