A Comparative Study of Graph Matching Algorithms in Computer Vision

Benchmark Results for “flow”

This page shows the benchmarks results for the dataset “flow”. The reported values, bounds and accuracies are averaged across all instances of the dataset.

Run time 1s

method avg value avg bound feasible optimal accuracy
dd-ls0 -2345.27 -2968.25 6 / 6 2 / 6
dd-ls3 -2059.06 -3030.04 6 / 6 1 / 6
dd-ls4 -2061.77 -3089.7 6 / 6 0 / 6
fgmd inf -inf 0 / 6 0 / 6
fm-bca -2838.06 -2898.35 6 / 6 5 / 6
fm -2838.19 -3435.54 6 / 6 5 / 6
fw -2828.06 -inf 6 / 6 4 / 6
ga inf -inf 0 / 6 0 / 6
hbp inf -inf 0 / 6 0 / 6
ipfps -766.428 -inf 6 / 6 0 / 6
ipfpu -512.097 -inf 6 / 6 0 / 6
lsm inf -inf 0 / 6 0 / 6
mp -2628.05 -2887.38 6 / 6 2 / 6
mp-fw inf -2964.53 6 / 6 5 / 6
mpm inf -inf 0 / 6 0 / 6
mp-mcf -2521.14 -2892.06 6 / 6 2 / 6
pm -31.6635 -inf 6 / 6 0 / 6
rrwm inf -inf 5 / 6 0 / 6
sm -138.712 -inf 6 / 6 0 / 6
smac 0 -inf 6 / 6 0 / 6

Run time 10s

method avg value avg bound feasible optimal accuracy
dd-ls0 -2819.27 -2853.72 6 / 6 4 / 6
dd-ls3 -2821.38 -2846.65 6 / 6 5 / 6
dd-ls4 -2767.38 -2863.45 6 / 6 4 / 6
fgmd inf -inf 0 / 6 0 / 6
fm-bca -2840 -2878.81 6 / 6 6 / 6
fm -2840 -3435.54 6 / 6 6 / 6
fw -2828.06 -inf 6 / 6 4 / 6
ga inf -inf 3 / 6 0 / 6
hbp inf -inf 0 / 6 0 / 6
ipfps -766.428 -inf 6 / 6 0 / 6
ipfpu -512.097 -inf 6 / 6 0 / 6
lsm inf -inf 3 / 6 0 / 6
mp -2674.1 -2881.54 6 / 6 2 / 6
mp-fw inf -2949.7 6 / 6 5 / 6
mpm inf -inf 1 / 6 0 / 6
mp-mcf -2719.47 -2868.97 6 / 6 2 / 6
pm -31.6635 -inf 6 / 6 0 / 6
rrwm -226.495 -inf 6 / 6 0 / 6
sm -138.712 -inf 6 / 6 0 / 6
smac 0 -inf 6 / 6 0 / 6

Run time 100s

method avg value avg bound feasible optimal accuracy
dd-ls0 -2819.27 -2853.72 6 / 6 4 / 6
dd-ls3 -2834.17 -2844.37 6 / 6 5 / 6
dd-ls4 -2834.74 -2842.7 6 / 6 5 / 6
fgmd inf -inf 0 / 6 0 / 6
fm-bca -2840 -2877.64 6 / 6 6 / 6
fm -2840 -3435.54 6 / 6 6 / 6
fw -2828.06 -inf 6 / 6 4 / 6
ga -2469.37 -inf 6 / 6 0 / 6
hbp inf -inf 0 / 6 0 / 6
ipfps -766.428 -inf 6 / 6 0 / 6
ipfpu -512.097 -inf 6 / 6 0 / 6
lsm 31042.3 -inf 6 / 6 0 / 6
mp -2690.36 -2881.05 6 / 6 3 / 6
mp-fw -2837.96 -2869.86 6 / 6 5 / 6
mpm inf -inf 3 / 6 0 / 6
mp-mcf -2748.86 -2854.26 6 / 6 3 / 6
pm -31.6635 -inf 6 / 6 0 / 6
rrwm -226.495 -inf 6 / 6 0 / 6
sm -138.712 -inf 6 / 6 0 / 6
smac 0 -inf 6 / 6 0 / 6

Run time 300s

method avg value avg bound feasible optimal accuracy
dd-ls0 -2819.27 -2853.72 6 / 6 4 / 6
dd-ls3 -2834.17 -2844.37 6 / 6 5 / 6
dd-ls4 -2834.74 -2842.68 6 / 6 5 / 6
fgmd inf -inf 0 / 6 0 / 6
fm-bca -2840 -2877.62 6 / 6 6 / 6
fm -2840 -3435.54 6 / 6 6 / 6
fw -2828.06 -inf 6 / 6 4 / 6
ga -2469.37 -inf 6 / 6 0 / 6
hbp inf -inf 0 / 6 0 / 6
ipfps -766.428 -inf 6 / 6 0 / 6
ipfpu -512.097 -inf 6 / 6 0 / 6
lsm 31042.3 -inf 6 / 6 0 / 6
mp -2690.36 -2881.05 6 / 6 3 / 6
mp-fw -2837.96 -2862.06 6 / 6 5 / 6
mpm inf -inf 3 / 6 0 / 6
mp-mcf -2788.94 -2850.9 6 / 6 3 / 6
pm -31.6635 -inf 6 / 6 0 / 6
rrwm -226.495 -inf 6 / 6 0 / 6
sm -138.712 -inf 6 / 6 0 / 6
smac 0 -inf 6 / 6 0 / 6

Per Instance Results

Results for individual instances of the dataset are also available: