A Comparative Study of Graph Matching Algorithms in Computer Vision

Benchmark Results for “motor15”

This page shows the benchmarks results for the dataset instance “motor15”. We consider solutions as optimal if the objective value is within a 0.1% range of the known optimum -32.3.

Run time 1s

method value bound optimal accuracy
dd-ls0 -32.3022 -32.3143 yes 100.00%
dd-ls3 -32.3022 -32.3044 yes 100.00%
dd-ls4 -25.0526 -36.7808 no 55.00%
fgmd inf -inf no
fm-bca -32.3022 -35.3027 yes 100.00%
fm -32.3022 -57.7832 yes 100.00%
fw -24.4734 -inf no 10.00%
ga -31.2236 -inf no 70.00%
hbp -32.3022 -36.3643 yes 100.00%
ipfps -30.0633 -inf no 55.00%
ipfpu -29.2331 -inf no 65.00%
lsm -26.7246 -inf no 45.00%
mp -32.3022 -34.9074 yes 100.00%
mp-fw -32.3022 -32.6799 yes 100.00%
mpm -15.0945 -inf no 5.00%
mp-mcf -32.3022 -32.5326 yes 100.00%
pm -18.7046 -inf no 10.00%
rrwm -30.2248 -inf no 60.00%
sm -31.2132 -inf no 85.00%
smac -23.6922 -inf no 40.00%

Run time 10s

method value bound optimal accuracy
dd-ls0 -32.3022 -32.3143 yes 100.00%
dd-ls3 -32.3022 -32.3044 yes 100.00%
dd-ls4 -32.3022 -32.3029 yes 100.00%
fgmd -32.0565 -inf no 85.00%
fm-bca -32.3022 -35.3027 yes 100.00%
fm -32.3022 -57.7832 yes 100.00%
fw -24.4734 -inf no 10.00%
ga -31.2236 -inf no 70.00%
hbp -32.3022 -36.3643 yes 100.00%
ipfps -30.0633 -inf no 55.00%
ipfpu -29.2331 -inf no 65.00%
lsm -26.7246 -inf no 45.00%
mp -32.3022 -34.9074 yes 100.00%
mp-fw -32.3022 -32.4747 yes 100.00%
mpm -15.0945 -inf no 5.00%
mp-mcf -32.3022 -32.4746 yes 100.00%
pm -18.7046 -inf no 10.00%
rrwm -30.2248 -inf no 60.00%
sm -31.2132 -inf no 85.00%
smac -23.6922 -inf no 40.00%

Run time 100s

method value bound optimal accuracy
dd-ls0 -32.3022 -32.3143 yes 100.00%
dd-ls3 -32.3022 -32.3044 yes 100.00%
dd-ls4 -32.3022 -32.3029 yes 100.00%
fgmd -32.0565 -inf no 85.00%
fm-bca -32.3022 -35.3027 yes 100.00%
fm -32.3022 -57.7832 yes 100.00%
fw -24.4734 -inf no 10.00%
ga -31.2236 -inf no 70.00%
hbp -32.3022 -36.3643 yes 100.00%
ipfps -30.0633 -inf no 55.00%
ipfpu -29.2331 -inf no 65.00%
lsm -26.7246 -inf no 45.00%
mp -32.3022 -34.9074 yes 100.00%
mp-fw -32.3022 -32.3022 yes 100.00%
mpm -15.0945 -inf no 5.00%
mp-mcf -32.3022 -32.3022 yes 100.00%
pm -18.7046 -inf no 10.00%
rrwm -30.2248 -inf no 60.00%
sm -31.2132 -inf no 85.00%
smac -23.6922 -inf no 40.00%

Run time 300s

method value bound optimal accuracy
dd-ls0 -32.3022 -32.3143 yes 100.00%
dd-ls3 -32.3022 -32.3044 yes 100.00%
dd-ls4 -32.3022 -32.3029 yes 100.00%
fgmd -32.0565 -inf no 85.00%
fm-bca -32.3022 -35.3027 yes 100.00%
fm -32.3022 -57.7832 yes 100.00%
fw -24.4734 -inf no 10.00%
ga -31.2236 -inf no 70.00%
hbp -32.3022 -36.3643 yes 100.00%
ipfps -30.0633 -inf no 55.00%
ipfpu -29.2331 -inf no 65.00%
lsm -26.7246 -inf no 45.00%
mp -32.3022 -34.9074 yes 100.00%
mp-fw -32.3022 -32.3022 yes 100.00%
mpm -15.0945 -inf no 5.00%
mp-mcf -32.3022 -32.3022 yes 100.00%
pm -18.7046 -inf no 10.00%
rrwm -30.2248 -inf no 60.00%
sm -31.2132 -inf no 85.00%
smac -23.6922 -inf no 40.00%

Other Results for this Dataset

Accumulated results for whole dataset: motor

Results for individual instances of the dataset: