A Comparative Study of Graph Matching Algorithms in Computer Vision

Benchmark Results for “caltech-small12”

This page shows the benchmarks results for the dataset instance “caltech-small12”. We consider solutions as optimal if the objective value is within a 0.1% range of the known optimum -758.394.

Run time 1s

method value bound optimal accuracy
dd-ls0 -758.394 -758.394 yes 100.00%
dd-ls3 -758.394 -758.394 yes 100.00%
dd-ls4 -758.394 -758.398 yes 100.00%
fgmd inf -inf no
fm-bca -758.394 -978.014 yes 100.00%
fm -758.394 -2224.26 yes 100.00%
fw 0 -inf no 0.00%
ga -668.711 -inf no 100.00%
hbp inf -inf no
ipfps -713.324 -inf no 100.00%
ipfpu -701.011 -inf no 100.00%
lsm 0 -inf no 0.00%
mp -715.025 -975.139 no 0.00%
mp-fw -758.394 -895.183 yes 100.00%
mpm -582.868 -inf no 0.00%
mp-mcf -702.048 -886.724 no 100.00%
pm -525.642 -inf no 66.67%
rrwm -744.215 -inf no 100.00%
sm -212.34 -inf no 0.00%
smac -317.481 -inf no 33.33%

Run time 10s

method value bound optimal accuracy
dd-ls0 -758.394 -758.394 yes 100.00%
dd-ls3 -758.394 -758.394 yes 100.00%
dd-ls4 -758.394 -758.394 yes 100.00%
fgmd -758.203 -inf yes 100.00%
fm-bca -758.394 -978.014 yes 100.00%
fm -758.394 -2224.26 yes 100.00%
fw 0 -inf no 0.00%
ga -668.711 -inf no 100.00%
hbp inf -inf no
ipfps -713.324 -inf no 100.00%
ipfpu -701.011 -inf no 100.00%
lsm 0 -inf no 0.00%
mp -715.025 -975.139 no 0.00%
mp-fw -758.394 -857.126 yes 100.00%
mpm -582.868 -inf no 0.00%
mp-mcf -702.048 -857.475 no 100.00%
pm -525.642 -inf no 66.67%
rrwm -744.215 -inf no 100.00%
sm -212.34 -inf no 0.00%
smac -317.481 -inf no 33.33%

Run time 100s

method value bound optimal accuracy
dd-ls0 -758.394 -758.394 yes 100.00%
dd-ls3 -758.394 -758.394 yes 100.00%
dd-ls4 -758.394 -758.394 yes 100.00%
fgmd -758.203 -inf yes 100.00%
fm-bca -758.394 -978.014 yes 100.00%
fm -758.394 -2224.26 yes 100.00%
fw 0 -inf no 0.00%
ga -668.711 -inf no 100.00%
hbp -752.323 -2206.79 no 100.00%
ipfps -713.324 -inf no 100.00%
ipfpu -701.011 -inf no 100.00%
lsm 0 -inf no 0.00%
mp -715.025 -975.139 no 0.00%
mp-fw -758.394 -852.26 yes 100.00%
mpm -582.868 -inf no 0.00%
mp-mcf -702.048 -855.033 no 100.00%
pm -525.642 -inf no 66.67%
rrwm -744.215 -inf no 100.00%
sm -212.34 -inf no 0.00%
smac -317.481 -inf no 33.33%

Run time 300s

method value bound optimal accuracy
dd-ls0 -758.394 -758.394 yes 100.00%
dd-ls3 -758.394 -758.394 yes 100.00%
dd-ls4 -758.394 -758.394 yes 100.00%
fgmd -758.203 -inf yes 100.00%
fm-bca -758.394 -978.014 yes 100.00%
fm -758.394 -2224.26 yes 100.00%
fw 0 -inf no 0.00%
ga -668.711 -inf no 100.00%
hbp -752.323 -2206.79 no 100.00%
ipfps -713.324 -inf no 100.00%
ipfpu -701.011 -inf no 100.00%
lsm 0 -inf no 0.00%
mp -715.025 -975.139 no 0.00%
mp-fw -758.394 -851.69 yes 100.00%
mpm -582.868 -inf no 0.00%
mp-mcf -702.048 -854.731 no 100.00%
pm -525.642 -inf no 66.67%
rrwm -744.215 -inf no 100.00%
sm -212.34 -inf no 0.00%
smac -317.481 -inf no 33.33%

Other Results for this Dataset

Accumulated results for whole dataset: caltech-small

Results for individual instances of the dataset: