A Comparative Study of Graph Matching Algorithms in Computer Vision

Benchmark Results for “caltech-small19”

This page shows the benchmarks results for the dataset instance “caltech-small19”. We consider solutions as optimal if the objective value is within a 0.1% range of the known optimum -5490.98.

Run time 1s

method value bound optimal accuracy
dd-ls0 -5490.98 -5491.03 yes 58.82%
dd-ls3 -5490.98 -5491.25 yes 58.82%
dd-ls4 -5286.39 -6377.45 no 70.59%
fgmd inf -inf no
fm-bca -5470.88 -6517.21 no 58.82%
fm -5490.98 -16207.7 yes 58.82%
fw 0 -inf no 0.00%
ga inf -inf no
hbp inf -inf no
ipfps -5490.98 -inf yes 58.82%
ipfpu -5490.98 -inf yes 58.82%
lsm 0 -inf no 0.00%
mp -5331.12 -6013.28 no 64.71%
mp-fw -5490.98 -6258.81 yes 58.82%
mpm -4961.41 -inf no 64.71%
mp-mcf -5440.15 -5868.12 no 58.82%
pm -5065.27 -inf no 52.94%
rrwm -5396.66 -inf no 58.82%
sm -3930.44 -inf no 64.71%
smac -4283.62 -inf no 58.82%

Run time 10s

method value bound optimal accuracy
dd-ls0 -5490.98 -5491.03 yes 58.82%
dd-ls3 -5490.98 -5491.25 yes 58.82%
dd-ls4 -5490.98 -5491.01 yes 58.82%
fgmd inf -inf no
fm-bca -5490.98 -6517.21 yes 58.82%
fm -5490.98 -16207.7 yes 58.82%
fw 0 -inf no 0.00%
ga -5075.75 -inf no 64.71%
hbp inf -inf no
ipfps -5490.98 -inf yes 58.82%
ipfpu -5490.98 -inf yes 58.82%
lsm 0 -inf no 0.00%
mp -5467.6 -6013.28 no 58.82%
mp-fw -5490.98 -5869.63 yes 58.82%
mpm -4961.41 -inf no 64.71%
mp-mcf -5490.98 -5671.42 yes 58.82%
pm -5065.27 -inf no 52.94%
rrwm -5396.66 -inf no 58.82%
sm -3930.44 -inf no 64.71%
smac -4283.62 -inf no 58.82%

Run time 100s

method value bound optimal accuracy
dd-ls0 -5490.98 -5491.03 yes 58.82%
dd-ls3 -5490.98 -5491.25 yes 58.82%
dd-ls4 -5490.98 -5491.01 yes 58.82%
fgmd -5490.98 -inf yes 58.82%
fm-bca -5490.98 -6517.21 yes 58.82%
fm -5490.98 -16207.7 yes 58.82%
fw 0 -inf no 0.00%
ga -5075.75 -inf no 64.71%
hbp -5318.94 -7266.94 no 58.82%
ipfps -5490.98 -inf yes 58.82%
ipfpu -5490.98 -inf yes 58.82%
lsm 0 -inf no 0.00%
mp -5486.93 -6013.28 yes 58.82%
mp-fw -5490.98 -5610.27 yes 58.82%
mpm -4961.41 -inf no 64.71%
mp-mcf -5490.98 -5605.44 yes 58.82%
pm -5065.27 -inf no 52.94%
rrwm -5396.66 -inf no 58.82%
sm -3930.44 -inf no 64.71%
smac -4283.62 -inf no 58.82%

Run time 300s

method value bound optimal accuracy
dd-ls0 -5490.98 -5491.03 yes 58.82%
dd-ls3 -5490.98 -5491.25 yes 58.82%
dd-ls4 -5490.98 -5491.01 yes 58.82%
fgmd -5490.98 -inf yes 58.82%
fm-bca -5490.98 -6517.21 yes 58.82%
fm -5490.98 -16207.7 yes 58.82%
fw 0 -inf no 0.00%
ga -5075.75 -inf no 64.71%
hbp -5318.94 -7266.94 no 58.82%
ipfps -5490.98 -inf yes 58.82%
ipfpu -5490.98 -inf yes 58.82%
lsm 0 -inf no 0.00%
mp -5486.93 -6013.28 yes 58.82%
mp-fw -5490.98 -5603.85 yes 58.82%
mpm -4961.41 -inf no 64.71%
mp-mcf -5490.98 -5601.44 yes 58.82%
pm -5065.27 -inf no 52.94%
rrwm -5396.66 -inf no 58.82%
sm -3930.44 -inf no 64.71%
smac -4283.62 -inf no 58.82%

Other Results for this Dataset

Accumulated results for whole dataset: caltech-small

Results for individual instances of the dataset: