A Comparative Study of Graph Matching Algorithms in Computer Vision

Benchmark Results for “car14”

This page shows the benchmarks results for the dataset instance “car14”. We consider solutions as optimal if the objective value is within a 0.1% range of the known optimum -97.96.

Run time 1s

method value bound optimal accuracy
dd-ls0 -97.9629 -97.963 yes 86.36%
dd-ls3 -62.2484 -107.802 no 59.09%
dd-ls4 -66.1912 -110.272 no 68.18%
fgmd inf -inf no
fm-bca -97.9629 -98.9499 yes 86.36%
fm -97.8869 -149.093 yes 84.09%
fw -96.1862 -inf no 77.27%
ga -96.1862 -inf no 77.27%
hbp inf -inf no
ipfps -97.9629 -inf yes 86.36%
ipfpu -95.3871 -inf no 75.00%
lsm -85.9866 -inf no 59.09%
mp -97.7716 -99.083 no 100.00%
mp-fw -97.9587 -99.0205 yes 88.64%
mpm inf -inf no
mp-mcf -97.9629 -98.7118 yes 86.36%
pm -45.8854 -inf no 20.45%
rrwm -97.8869 -inf yes 84.09%
sm -94.7705 -inf no 88.64%
smac -81.1432 -inf no 59.09%

Run time 10s

method value bound optimal accuracy
dd-ls0 -97.9629 -97.963 yes 86.36%
dd-ls3 -97.9629 -98.0892 yes 86.36%
dd-ls4 -66.1912 -105.602 no 68.18%
fgmd -97.9587 -inf yes 88.64%
fm-bca -97.9629 -98.9499 yes 86.36%
fm -97.8869 -149.093 yes 84.09%
fw -96.1862 -inf no 77.27%
ga -96.1862 -inf no 77.27%
hbp -97.9629 -101.64 yes 86.36%
ipfps -97.9629 -inf yes 86.36%
ipfpu -95.3871 -inf no 75.00%
lsm -85.9866 -inf no 59.09%
mp -97.7716 -98.9992 no 100.00%
mp-fw -97.9629 -98.5631 yes 86.36%
mpm -76.1275 -inf no 72.73%
mp-mcf -97.9629 -98.5558 yes 86.36%
pm -45.8854 -inf no 20.45%
rrwm -97.8869 -inf yes 84.09%
sm -94.7705 -inf no 88.64%
smac -81.1432 -inf no 59.09%

Run time 100s

method value bound optimal accuracy
dd-ls0 -97.9629 -97.963 yes 86.36%
dd-ls3 -97.9629 -97.9629 yes 86.36%
dd-ls4 -97.9629 -98.0224 yes 86.36%
fgmd -97.9587 -inf yes 88.64%
fm-bca -97.9629 -98.9499 yes 86.36%
fm -97.8869 -149.093 yes 84.09%
fw -96.1862 -inf no 77.27%
ga -96.1862 -inf no 77.27%
hbp -97.9629 -101.64 yes 86.36%
ipfps -97.9629 -inf yes 86.36%
ipfpu -95.3871 -inf no 75.00%
lsm -85.9866 -inf no 59.09%
mp -97.7716 -98.9907 no 100.00%
mp-fw -97.9629 -98.3355 yes 86.36%
mpm -76.1275 -inf no 72.73%
mp-mcf -97.9629 -98.3251 yes 86.36%
pm -45.8854 -inf no 20.45%
rrwm -97.8869 -inf yes 84.09%
sm -94.7705 -inf no 88.64%
smac -81.1432 -inf no 59.09%

Run time 300s

method value bound optimal accuracy
dd-ls0 -97.9629 -97.963 yes 86.36%
dd-ls3 -97.9629 -97.9629 yes 86.36%
dd-ls4 -97.9629 -97.963 yes 86.36%
fgmd -97.9587 -inf yes 88.64%
fm-bca -97.9629 -98.9499 yes 86.36%
fm -97.8869 -149.093 yes 84.09%
fw -96.1862 -inf no 77.27%
ga -96.1862 -inf no 77.27%
hbp -97.9629 -101.64 yes 86.36%
ipfps -97.9629 -inf yes 86.36%
ipfpu -95.3871 -inf no 75.00%
lsm -85.9866 -inf no 59.09%
mp -97.7716 -98.9894 no 100.00%
mp-fw -97.9629 -98.3355 yes 86.36%
mpm -76.1275 -inf no 72.73%
mp-mcf -97.9629 -98.3183 yes 86.36%
pm -45.8854 -inf no 20.45%
rrwm -97.8869 -inf yes 84.09%
sm -94.7705 -inf no 88.64%
smac -81.1432 -inf no 59.09%

Other Results for this Dataset

Accumulated results for whole dataset: car

Results for individual instances of the dataset: