A Comparative Study of Graph Matching Algorithms in Computer Vision

Benchmark Results for “car24”

This page shows the benchmarks results for the dataset instance “car24”. We consider solutions as optimal if the objective value is within a 0.1% range of the known optimum -64.58.

Run time 1s

method value bound optimal accuracy
dd-ls0 -64.5752 -64.5758 yes 90.32%
dd-ls3 -59.3602 -66.8803 no 77.42%
dd-ls4 -38.6254 -74.1094 no 48.39%
fgmd inf -inf no
fm-bca -64.5752 -65.0735 yes 90.32%
fm -64.5752 -98.5397 yes 90.32%
fw -45.3759 -inf no 12.90%
ga -64.5752 -inf yes 90.32%
hbp -64.5752 -67.8455 yes 90.32%
ipfps -61.0948 -inf no 80.65%
ipfpu -58.5322 -inf no 64.52%
lsm -45.4157 -inf no 54.84%
mp -64.5752 -65.0224 yes 90.32%
mp-fw -64.5752 -65.0106 yes 90.32%
mpm -49.6633 -inf no 61.29%
mp-mcf -64.5752 -64.5752 yes 90.32%
pm -31.8172 -inf no 12.90%
rrwm -63.9551 -inf no 100.00%
sm -62.542 -inf no 83.87%
smac -34.9008 -inf no 22.58%

Run time 10s

method value bound optimal accuracy
dd-ls0 -64.5752 -64.5758 yes 90.32%
dd-ls3 -64.5752 -64.5764 yes 90.32%
dd-ls4 -64.5752 -66.0937 yes 90.32%
fgmd -64.5752 -inf yes 90.32%
fm-bca -64.5752 -65.0734 yes 90.32%
fm -64.5752 -98.5397 yes 90.32%
fw -45.3759 -inf no 12.90%
ga -64.5752 -inf yes 90.32%
hbp -64.5752 -67.8455 yes 90.32%
ipfps -61.0948 -inf no 80.65%
ipfpu -58.5322 -inf no 64.52%
lsm -45.4157 -inf no 54.84%
mp -64.5752 -65.0223 yes 90.32%
mp-fw -64.5752 -64.5752 yes 90.32%
mpm -49.6633 -inf no 61.29%
mp-mcf -64.5752 -64.5752 yes 90.32%
pm -31.8172 -inf no 12.90%
rrwm -63.9551 -inf no 100.00%
sm -62.542 -inf no 83.87%
smac -34.9008 -inf no 22.58%

Run time 100s

method value bound optimal accuracy
dd-ls0 -64.5752 -64.5758 yes 90.32%
dd-ls3 -64.5752 -64.5764 yes 90.32%
dd-ls4 -64.5752 -64.5763 yes 90.32%
fgmd -64.5752 -inf yes 90.32%
fm-bca -64.5752 -65.0734 yes 90.32%
fm -64.5752 -98.5397 yes 90.32%
fw -45.3759 -inf no 12.90%
ga -64.5752 -inf yes 90.32%
hbp -64.5752 -67.8455 yes 90.32%
ipfps -61.0948 -inf no 80.65%
ipfpu -58.5322 -inf no 64.52%
lsm -45.4157 -inf no 54.84%
mp -64.5752 -65.0223 yes 90.32%
mp-fw -64.5752 -64.5752 yes 90.32%
mpm -49.6633 -inf no 61.29%
mp-mcf -64.5752 -64.5752 yes 90.32%
pm -31.8172 -inf no 12.90%
rrwm -63.9551 -inf no 100.00%
sm -62.542 -inf no 83.87%
smac -34.9008 -inf no 22.58%

Run time 300s

method value bound optimal accuracy
dd-ls0 -64.5752 -64.5758 yes 90.32%
dd-ls3 -64.5752 -64.5764 yes 90.32%
dd-ls4 -64.5752 -64.5763 yes 90.32%
fgmd -64.5752 -inf yes 90.32%
fm-bca -64.5752 -65.0734 yes 90.32%
fm -64.5752 -98.5397 yes 90.32%
fw -45.3759 -inf no 12.90%
ga -64.5752 -inf yes 90.32%
hbp -64.5752 -67.8455 yes 90.32%
ipfps -61.0948 -inf no 80.65%
ipfpu -58.5322 -inf no 64.52%
lsm -45.4157 -inf no 54.84%
mp -64.5752 -65.0223 yes 90.32%
mp-fw -64.5752 -64.5752 yes 90.32%
mpm -49.6633 -inf no 61.29%
mp-mcf -64.5752 -64.5752 yes 90.32%
pm -31.8172 -inf no 12.90%
rrwm -63.9551 -inf no 100.00%
sm -62.542 -inf no 83.87%
smac -34.9008 -inf no 22.58%

Other Results for this Dataset

Accumulated results for whole dataset: car

Results for individual instances of the dataset: