A Comparative Study of Graph Matching Algorithms in Computer Vision

Benchmark Results for “motor14”

This page shows the benchmarks results for the dataset instance “motor14”. We consider solutions as optimal if the objective value is within a 0.1% range of the known optimum -43.8.

Run time 1s

method value bound optimal accuracy
dd-ls0 -43.8014 -44.2361 yes 73.08%
dd-ls3 -39.6182 -46.7633 no 69.23%
dd-ls4 -33.3159 -53.8865 no 57.69%
fgmd inf -inf no
fm-bca -43.8014 -47.9009 yes 73.08%
fm -43.8014 -80.0685 yes 73.08%
fw -34.7035 -inf no 26.92%
ga -42.8896 -inf no 65.38%
hbp inf -inf no
ipfps -39.0976 -inf no 50.00%
ipfpu -35.8787 -inf no 30.77%
lsm -26.7164 -inf no 26.92%
mp -43.3726 -46.8957 no 65.38%
mp-fw -43.6199 -45.9015 no 80.77%
mpm -27.2619 -inf no 3.85%
mp-mcf -43.469 -45.5743 no 84.62%
pm -25.4578 -inf no 3.85%
rrwm -41.5718 -inf no 57.69%
sm -38.4068 -inf no 53.85%
smac -36.7966 -inf no 30.77%

Run time 10s

method value bound optimal accuracy
dd-ls0 -43.8014 -44.2361 yes 73.08%
dd-ls3 -43.8014 -43.8824 yes 73.08%
dd-ls4 -41.5765 -45.6708 no 65.38%
fgmd -43.698 -inf no 80.77%
fm-bca -43.8014 -47.9009 yes 73.08%
fm -43.8014 -80.0685 yes 73.08%
fw -34.7035 -inf no 26.92%
ga -42.8896 -inf no 65.38%
hbp -43.8014 -48.8096 yes 73.08%
ipfps -39.0976 -inf no 50.00%
ipfpu -35.8787 -inf no 30.77%
lsm -26.7164 -inf no 26.92%
mp -43.6199 -46.8954 no 80.77%
mp-fw -43.8014 -44.63 yes 73.08%
mpm -27.2619 -inf no 3.85%
mp-mcf -43.7162 -44.4632 no 100.00%
pm -25.4578 -inf no 3.85%
rrwm -41.5718 -inf no 57.69%
sm -38.4068 -inf no 53.85%
smac -36.7966 -inf no 30.77%

Run time 100s

method value bound optimal accuracy
dd-ls0 -43.8014 -44.2361 yes 73.08%
dd-ls3 -43.8014 -43.8805 yes 73.08%
dd-ls4 -43.8014 -43.8015 yes 73.08%
fgmd -43.698 -inf no 80.77%
fm-bca -43.8014 -47.9009 yes 73.08%
fm -43.8014 -80.0685 yes 73.08%
fw -34.7035 -inf no 26.92%
ga -42.8896 -inf no 65.38%
hbp -43.8014 -48.8096 yes 73.08%
ipfps -39.0976 -inf no 50.00%
ipfpu -35.8787 -inf no 30.77%
lsm -26.7164 -inf no 26.92%
mp -43.6199 -46.8954 no 80.77%
mp-fw -43.8014 -43.8774 yes 73.08%
mpm -27.2619 -inf no 3.85%
mp-mcf -43.7162 -43.8956 no 100.00%
pm -25.4578 -inf no 3.85%
rrwm -41.5718 -inf no 57.69%
sm -38.4068 -inf no 53.85%
smac -36.7966 -inf no 30.77%

Run time 300s

method value bound optimal accuracy
dd-ls0 -43.8014 -44.2361 yes 73.08%
dd-ls3 -43.8014 -43.8805 yes 73.08%
dd-ls4 -43.8014 -43.8015 yes 73.08%
fgmd -43.698 -inf no 80.77%
fm-bca -43.8014 -47.9009 yes 73.08%
fm -43.8014 -80.0685 yes 73.08%
fw -34.7035 -inf no 26.92%
ga -42.8896 -inf no 65.38%
hbp -43.8014 -48.8096 yes 73.08%
ipfps -39.0976 -inf no 50.00%
ipfpu -35.8787 -inf no 30.77%
lsm -26.7164 -inf no 26.92%
mp -43.6199 -46.8954 no 80.77%
mp-fw -43.8014 -43.8763 yes 73.08%
mpm -27.2619 -inf no 3.85%
mp-mcf -43.7162 -43.816 no 100.00%
pm -25.4578 -inf no 3.85%
rrwm -41.5718 -inf no 57.69%
sm -38.4068 -inf no 53.85%
smac -36.7966 -inf no 30.77%

Other Results for this Dataset

Accumulated results for whole dataset: motor

Results for individual instances of the dataset: