A Comparative Study of Graph Matching Algorithms in Computer Vision

Benchmark Results for “car10”

This page shows the benchmarks results for the dataset instance “car10”. We consider solutions as optimal if the objective value is within a 0.1% range of the known optimum -57.62.

Run time 1s

method value bound optimal accuracy
dd-ls0 -57.6169 -57.6317 yes 100.00%
dd-ls3 -57.6169 -58.4723 yes 100.00%
dd-ls4 -34.8194 -65.896 no 50.00%
fgmd inf -inf no
fm-bca -57.6169 -57.6169 yes 100.00%
fm -57.6169 -90.3719 yes 100.00%
fw -50.7314 -inf no 71.43%
ga -57.6169 -inf yes 100.00%
hbp -57.6169 -60.5104 yes 100.00%
ipfps -54.0903 -inf no 78.57%
ipfpu -55.2326 -inf no 85.71%
lsm -28.6794 -inf no 10.71%
mp -57.6169 -57.6169 yes 100.00%
mp-fw -57.6169 -57.6169 yes 100.00%
mpm -43.5935 -inf no 60.71%
mp-mcf -57.6169 -57.6169 yes 100.00%
pm -26.4024 -inf no 17.86%
rrwm -57.6169 -inf yes 100.00%
sm -55.117 -inf no 85.71%
smac -47.6535 -inf no 60.71%

Run time 10s

method value bound optimal accuracy
dd-ls0 -57.6169 -57.6317 yes 100.00%
dd-ls3 -57.6169 -57.62 yes 100.00%
dd-ls4 -57.6169 -57.6273 yes 100.00%
fgmd -57.6169 -inf yes 100.00%
fm-bca -57.6169 -57.6169 yes 100.00%
fm -57.6169 -90.3719 yes 100.00%
fw -50.7314 -inf no 71.43%
ga -57.6169 -inf yes 100.00%
hbp -57.6169 -60.5104 yes 100.00%
ipfps -54.0903 -inf no 78.57%
ipfpu -55.2326 -inf no 85.71%
lsm -28.6794 -inf no 10.71%
mp -57.6169 -57.6169 yes 100.00%
mp-fw -57.6169 -57.6169 yes 100.00%
mpm -43.5935 -inf no 60.71%
mp-mcf -57.6169 -57.6169 yes 100.00%
pm -26.4024 -inf no 17.86%
rrwm -57.6169 -inf yes 100.00%
sm -55.117 -inf no 85.71%
smac -47.6535 -inf no 60.71%

Run time 100s

method value bound optimal accuracy
dd-ls0 -57.6169 -57.6317 yes 100.00%
dd-ls3 -57.6169 -57.62 yes 100.00%
dd-ls4 -57.6169 -57.6243 yes 100.00%
fgmd -57.6169 -inf yes 100.00%
fm-bca -57.6169 -57.6169 yes 100.00%
fm -57.6169 -90.3719 yes 100.00%
fw -50.7314 -inf no 71.43%
ga -57.6169 -inf yes 100.00%
hbp -57.6169 -60.5104 yes 100.00%
ipfps -54.0903 -inf no 78.57%
ipfpu -55.2326 -inf no 85.71%
lsm -28.6794 -inf no 10.71%
mp -57.6169 -57.6169 yes 100.00%
mp-fw -57.6169 -57.6169 yes 100.00%
mpm -43.5935 -inf no 60.71%
mp-mcf -57.6169 -57.6169 yes 100.00%
pm -26.4024 -inf no 17.86%
rrwm -57.6169 -inf yes 100.00%
sm -55.117 -inf no 85.71%
smac -47.6535 -inf no 60.71%

Run time 300s

method value bound optimal accuracy
dd-ls0 -57.6169 -57.6317 yes 100.00%
dd-ls3 -57.6169 -57.62 yes 100.00%
dd-ls4 -57.6169 -57.6243 yes 100.00%
fgmd -57.6169 -inf yes 100.00%
fm-bca -57.6169 -57.6169 yes 100.00%
fm -57.6169 -90.3719 yes 100.00%
fw -50.7314 -inf no 71.43%
ga -57.6169 -inf yes 100.00%
hbp -57.6169 -60.5104 yes 100.00%
ipfps -54.0903 -inf no 78.57%
ipfpu -55.2326 -inf no 85.71%
lsm -28.6794 -inf no 10.71%
mp -57.6169 -57.6169 yes 100.00%
mp-fw -57.6169 -57.6169 yes 100.00%
mpm -43.5935 -inf no 60.71%
mp-mcf -57.6169 -57.6169 yes 100.00%
pm -26.4024 -inf no 17.86%
rrwm -57.6169 -inf yes 100.00%
sm -55.117 -inf no 85.71%
smac -47.6535 -inf no 60.71%

Other Results for this Dataset

Accumulated results for whole dataset: car

Results for individual instances of the dataset: