A Comparative Study of Graph Matching Algorithms in Computer Vision

Benchmark Results for “car15”

This page shows the benchmarks results for the dataset instance “car15”. We consider solutions as optimal if the objective value is within a 0.1% range of the known optimum -66.89.

Run time 1s

method value bound optimal accuracy
dd-ls0 -66.894 -66.8941 yes 100.00%
dd-ls3 -66.894 -66.8958 yes 100.00%
dd-ls4 -66.347 -68.2129 no 85.71%
fgmd inf -inf no
fm-bca -66.894 -67.0075 yes 100.00%
fm -66.894 -91.6044 yes 100.00%
fw -65.9181 -inf no 82.14%
ga -66.368 -inf no 89.29%
hbp -66.894 -67.4599 yes 100.00%
ipfps -66.368 -inf no 89.29%
ipfpu -66.368 -inf no 89.29%
lsm -65.4014 -inf no 82.14%
mp -66.894 -66.894 yes 100.00%
mp-fw -66.894 -66.894 yes 100.00%
mpm -57.8007 -inf no 85.71%
mp-mcf -66.894 -66.894 yes 100.00%
pm -33.5584 -inf no 25.00%
rrwm -66.368 -inf no 89.29%
sm -66.347 -inf no 85.71%
smac -66.368 -inf no 89.29%

Run time 10s

method value bound optimal accuracy
dd-ls0 -66.894 -66.8941 yes 100.00%
dd-ls3 -66.894 -66.8958 yes 100.00%
dd-ls4 -66.894 -66.8957 yes 100.00%
fgmd -66.894 -inf yes 100.00%
fm-bca -66.894 -67.0075 yes 100.00%
fm -66.894 -91.6044 yes 100.00%
fw -65.9181 -inf no 82.14%
ga -66.368 -inf no 89.29%
hbp -66.894 -67.4599 yes 100.00%
ipfps -66.368 -inf no 89.29%
ipfpu -66.368 -inf no 89.29%
lsm -65.4014 -inf no 82.14%
mp -66.894 -66.894 yes 100.00%
mp-fw -66.894 -66.894 yes 100.00%
mpm -57.8007 -inf no 85.71%
mp-mcf -66.894 -66.894 yes 100.00%
pm -33.5584 -inf no 25.00%
rrwm -66.368 -inf no 89.29%
sm -66.347 -inf no 85.71%
smac -66.368 -inf no 89.29%

Run time 100s

method value bound optimal accuracy
dd-ls0 -66.894 -66.8941 yes 100.00%
dd-ls3 -66.894 -66.8958 yes 100.00%
dd-ls4 -66.894 -66.8957 yes 100.00%
fgmd -66.894 -inf yes 100.00%
fm-bca -66.894 -67.0075 yes 100.00%
fm -66.894 -91.6044 yes 100.00%
fw -65.9181 -inf no 82.14%
ga -66.368 -inf no 89.29%
hbp -66.894 -67.4599 yes 100.00%
ipfps -66.368 -inf no 89.29%
ipfpu -66.368 -inf no 89.29%
lsm -65.4014 -inf no 82.14%
mp -66.894 -66.894 yes 100.00%
mp-fw -66.894 -66.894 yes 100.00%
mpm -57.8007 -inf no 85.71%
mp-mcf -66.894 -66.894 yes 100.00%
pm -33.5584 -inf no 25.00%
rrwm -66.368 -inf no 89.29%
sm -66.347 -inf no 85.71%
smac -66.368 -inf no 89.29%

Run time 300s

method value bound optimal accuracy
dd-ls0 -66.894 -66.8941 yes 100.00%
dd-ls3 -66.894 -66.8958 yes 100.00%
dd-ls4 -66.894 -66.8957 yes 100.00%
fgmd -66.894 -inf yes 100.00%
fm-bca -66.894 -67.0075 yes 100.00%
fm -66.894 -91.6044 yes 100.00%
fw -65.9181 -inf no 82.14%
ga -66.368 -inf no 89.29%
hbp -66.894 -67.4599 yes 100.00%
ipfps -66.368 -inf no 89.29%
ipfpu -66.368 -inf no 89.29%
lsm -65.4014 -inf no 82.14%
mp -66.894 -66.894 yes 100.00%
mp-fw -66.894 -66.894 yes 100.00%
mpm -57.8007 -inf no 85.71%
mp-mcf -66.894 -66.894 yes 100.00%
pm -33.5584 -inf no 25.00%
rrwm -66.368 -inf no 89.29%
sm -66.347 -inf no 85.71%
smac -66.368 -inf no 89.29%

Other Results for this Dataset

Accumulated results for whole dataset: car

Results for individual instances of the dataset: