A Comparative Study of Graph Matching Algorithms in Computer Vision

Benchmark Results for “car17”

This page shows the benchmarks results for the dataset instance “car17”. We consider solutions as optimal if the objective value is within a 0.1% range of the known optimum -57.09.

Run time 1s

method value bound optimal accuracy
dd-ls0 -57.0892 -57.0987 yes 92.59%
dd-ls3 -47.9749 -60.1226 no 70.37%
dd-ls4 -36.0391 -63.9496 no 51.85%
fgmd inf -inf no
fm-bca -57.0892 -57.0892 yes 92.59%
fm -57.0892 -83.0876 yes 92.59%
fw -52.307 -inf no 62.96%
ga -52.2979 -inf no 62.96%
hbp -57.0892 -58.8315 yes 92.59%
ipfps -54.6507 -inf no 77.78%
ipfpu -53.0809 -inf no 77.78%
lsm -48.1228 -inf no 51.85%
mp -57.0892 -57.0892 yes 92.59%
mp-fw -57.0892 -57.0892 yes 92.59%
mpm -51.1951 -inf no 51.85%
mp-mcf -57.0892 -57.0892 yes 92.59%
pm -35.3629 -inf no 37.04%
rrwm -56.7714 -inf no 88.89%
sm -53.0809 -inf no 77.78%
smac -30.6798 -inf no 33.33%

Run time 10s

method value bound optimal accuracy
dd-ls0 -57.0892 -57.0987 yes 92.59%
dd-ls3 -57.0892 -57.0934 yes 92.59%
dd-ls4 -55.5474 -57.5729 no 85.19%
fgmd -57.0892 -inf yes 92.59%
fm-bca -57.0892 -57.0892 yes 92.59%
fm -57.0892 -83.0876 yes 92.59%
fw -52.307 -inf no 62.96%
ga -52.2979 -inf no 62.96%
hbp -57.0892 -58.8315 yes 92.59%
ipfps -54.6507 -inf no 77.78%
ipfpu -53.0809 -inf no 77.78%
lsm -48.1228 -inf no 51.85%
mp -57.0892 -57.0892 yes 92.59%
mp-fw -57.0892 -57.0892 yes 92.59%
mpm -51.1951 -inf no 51.85%
mp-mcf -57.0892 -57.0892 yes 92.59%
pm -35.3629 -inf no 37.04%
rrwm -56.7714 -inf no 88.89%
sm -53.0809 -inf no 77.78%
smac -30.6798 -inf no 33.33%

Run time 100s

method value bound optimal accuracy
dd-ls0 -57.0892 -57.0987 yes 92.59%
dd-ls3 -57.0892 -57.0934 yes 92.59%
dd-ls4 -57.0892 -57.0919 yes 92.59%
fgmd -57.0892 -inf yes 92.59%
fm-bca -57.0892 -57.0892 yes 92.59%
fm -57.0892 -83.0876 yes 92.59%
fw -52.307 -inf no 62.96%
ga -52.2979 -inf no 62.96%
hbp -57.0892 -58.8315 yes 92.59%
ipfps -54.6507 -inf no 77.78%
ipfpu -53.0809 -inf no 77.78%
lsm -48.1228 -inf no 51.85%
mp -57.0892 -57.0892 yes 92.59%
mp-fw -57.0892 -57.0892 yes 92.59%
mpm -51.1951 -inf no 51.85%
mp-mcf -57.0892 -57.0892 yes 92.59%
pm -35.3629 -inf no 37.04%
rrwm -56.7714 -inf no 88.89%
sm -53.0809 -inf no 77.78%
smac -30.6798 -inf no 33.33%

Run time 300s

method value bound optimal accuracy
dd-ls0 -57.0892 -57.0987 yes 92.59%
dd-ls3 -57.0892 -57.0934 yes 92.59%
dd-ls4 -57.0892 -57.0919 yes 92.59%
fgmd -57.0892 -inf yes 92.59%
fm-bca -57.0892 -57.0892 yes 92.59%
fm -57.0892 -83.0876 yes 92.59%
fw -52.307 -inf no 62.96%
ga -52.2979 -inf no 62.96%
hbp -57.0892 -58.8315 yes 92.59%
ipfps -54.6507 -inf no 77.78%
ipfpu -53.0809 -inf no 77.78%
lsm -48.1228 -inf no 51.85%
mp -57.0892 -57.0892 yes 92.59%
mp-fw -57.0892 -57.0892 yes 92.59%
mpm -51.1951 -inf no 51.85%
mp-mcf -57.0892 -57.0892 yes 92.59%
pm -35.3629 -inf no 37.04%
rrwm -56.7714 -inf no 88.89%
sm -53.0809 -inf no 77.78%
smac -30.6798 -inf no 33.33%

Other Results for this Dataset

Accumulated results for whole dataset: car

Results for individual instances of the dataset: