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FCGF #36

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Tracked by #32
fdila opened this issue Oct 9, 2023 · 3 comments
Closed
Tracked by #32

FCGF #36

fdila opened this issue Oct 9, 2023 · 3 comments
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fdila commented Oct 9, 2023

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@fdila fdila mentioned this issue Oct 9, 2023
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fdila commented Oct 27, 2023

@simone-fontana la parte di downsampling in FCGF è fatta "dentro" alla rete, quindi dargli le pc già downsamplate viene difficile. Se per te non è un problema teniamo a mente che i tempi di FCGF includono già i tempi di preprocessing e amen.

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va bene

@fdila fdila self-assigned this Nov 2, 2023
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fdila commented Nov 2, 2023

Risultati rete trainata su 3DMatch e voxel 5cm:

                      FastGlobal                           RANSAC                           TEASER                      
                          median     0.75 Q     0.95 Q     median     0.75 Q     0.95 Q     median     0.75 Q     0.95 Q
sequence                                                                                                                
plain                   0.938136   2.005102   2.631463   6.976526   9.313211  13.389405   1.405338   2.470591   3.288897
stairs                  0.154247   1.821620   4.379799   0.069109   3.211343   7.466637   0.046745   1.743021   5.535536
apartment               0.543761   1.594793   1.821829   2.563842   4.000031   4.927655   1.528035   1.863819   2.310892
hauptgebaude            0.708322   1.201353   2.036099   1.579307   2.161808   3.410643   0.808982   1.581263   2.097434
wood_autumn             0.180761   0.377423   0.722061   2.996062   3.982941   5.429485   0.223754   0.652095   1.420775
wood_summer             0.184317   0.352695   0.742734   2.934619   3.729510   5.233264   0.047828   0.334315   0.939352
gazebo_summer           0.111410   0.516751   1.916106   2.185892   3.027320   4.742395   0.020106   0.142432   2.389263
gazebo_winter           0.122339   0.401932   1.517154   2.542091   4.251594   5.657062   0.021695   0.075703   2.060721
box_met                 7.816196  10.205680  12.949845   7.605549  10.665932  13.788829   8.062238  10.232836  14.237900
p2at_met                5.793552   8.585979  10.444907   9.459152  12.570445  17.480945   6.306328   9.096823  12.312054
planetary_map          29.777008  41.525965  66.695854  11.082039  15.633464  21.161421  41.196269  57.255610  96.314408
pioneer_slam            0.053000   0.097357   1.541781   0.074213   0.125672   0.619870   0.043302   0.073780   0.175480
pioneer_slam3           0.035195   0.049915   0.086339   0.031594   0.045776   0.084603   0.025272   0.037901   0.065894
long_office_household   0.050979   0.090866   0.493257   0.082319   0.136686   0.257110   0.047857   0.079650   0.256304
urban05                 1.241746   1.727539   2.931804   2.419662   3.621642   5.292492   2.280194   3.546006   6.852614
Total                   0.347795   1.932486  19.709274   2.570984   5.157592  13.030998   0.586081   2.605261  26.860030

Risultati rete trainata su 3DMatch e voxel 10cm

                      FastGlobal                           RANSAC                           TEASER                       
                          median     0.75 Q     0.95 Q     median     0.75 Q     0.95 Q     median     0.75 Q      0.95 Q
sequence                                                                                                                 
plain                   0.597780   1.656912   2.382486   1.514435   6.436771  12.325442   0.344924   2.377845    3.333751
stairs                  0.036811   0.090851   2.825558   0.052716   0.079292   3.071221   0.022754   0.042422    4.967616
apartment               0.038434   0.101439   1.464607   0.041527   0.057631   1.313911   0.030790   0.062779    1.906817
hauptgebaude            0.552058   1.107298   2.039138   0.582307   1.405502   2.116125   0.749766   1.559828    2.108142
wood_autumn             0.106837   0.179256   0.504860   0.925567   3.005069   4.605184   0.029844   0.051393    0.428440
wood_summer             0.107099   0.230488   0.603625   0.105439   2.129163   4.187620   0.027276   0.043449    0.131803
gazebo_summer           0.054449   0.188757   1.591873   0.031274   0.064318   2.647929   0.018221   0.037935    0.165141
gazebo_winter           0.080716   0.165176   0.680771   0.046306   0.143514   2.897303   0.018652   0.027639    0.061361
box_met                 7.720765   9.857213  12.891071   7.442940  10.039520  13.788829   7.799760  10.247488   14.580992
p2at_met                4.303695   7.595060  11.210134   8.812610  12.503054  17.480945   5.700617   8.431981   14.194795
planetary_map          30.212441  41.740321  67.314502  11.082039  15.633464  21.705043  52.365035  71.922938  104.371491
pioneer_slam            0.112919   0.301158  10.345709   0.132799   0.271919   1.508851   0.111063   0.318252    1.601530
pioneer_slam3           0.053447   0.076573   0.182434   0.070747   0.111163   0.147353   0.059636   0.090565    0.182752
long_office_household   0.219692   1.883716  10.458442   0.150460   0.481983  12.388440   0.175515   0.863481    2.546163
urban05                 1.169354   1.834209   3.800783   2.565082   3.748179   5.349143   3.047741   4.190867    7.472837
Total                   0.221242   1.949110  18.421129   0.208328   4.000008  13.030998   0.085660   2.480437   31.100357

Risultati rete trainata su KITTI e voxel 20cm

                      FastGlobal                           RANSAC                           TEASER                       
                          median     0.75 Q     0.95 Q     median     0.75 Q     0.95 Q     median     0.75 Q      0.95 Q
sequence                                                                                                                 
plain                   2.995284   4.699180  11.170082   7.556038  11.758134  21.634127  10.159259  18.658032   27.207103
stairs                  2.230154   3.247184   6.119943   2.213172   3.073523   7.787511   2.804123   4.059326    8.469584
apartment               1.472579   1.653920   1.952687   1.456889   1.722049   2.023951   1.705223   1.942153    2.627093
hauptgebaude            1.932939   4.261249   8.139165   3.081070   5.874283  10.237390   4.566932   6.595268   10.123213
wood_autumn             2.139908   3.256552   4.824175   2.526319   3.504175   4.995303   3.153408   4.419199    5.618071
wood_summer             2.047932   3.133834   4.702709   2.627630   3.416935   5.151698   2.643194   3.709514    5.347951
gazebo_summer           1.902279   3.430673   5.013112   2.847820   4.277244   6.544231   3.966024   5.684268    8.729301
gazebo_winter           1.684497   3.275104   5.936449   3.309818   4.936914   7.526194   4.424482   6.144897   10.489026
box_met                 7.721250  10.171262  14.446453  10.052135  14.173341  19.664440  13.273010  18.655982   32.609557
p2at_met                7.047958   9.260775  14.672333  10.289515  18.726752  31.561148  13.989623  23.057033   35.222332
planetary_map          29.320657  42.774431  67.462023  14.241034  24.894397  58.405375  41.609434  59.498044  103.929268
pioneer_slam            6.102635   8.144102  12.648261   2.985687  10.912835  16.653181   5.530789  11.590763   16.376516
pioneer_slam3           5.605634   7.090943   8.569288   5.214027  10.415348  14.960140   9.385063  13.627405   18.224610
long_office_household   3.997233   7.341667  11.541364   2.248239   9.758750  21.459495   3.143243  10.053349   17.851040
urban05                 1.863163   3.307898   4.944633   2.859044   4.337318   8.616644   3.746452   6.436595   14.085277
Total                   3.083809   6.650268  18.719003   3.412639   8.182985  20.125742   4.721543  10.845981   34.234691

Rete trainata su KITTI e voxel 10cm:

                      FastGlobal                           RANSAC                           TEASER                      
                          median     0.75 Q     0.95 Q     median     0.75 Q     0.95 Q     median     0.75 Q     0.95 Q
sequence                                                                                                                
plain                   3.168365   6.435212  11.512060   6.930330   9.577429  16.626758   9.366707  13.926475  23.328162
stairs                  2.210233   3.326611   5.514269   2.441589   3.327577   7.780266   2.930180   4.484188   8.081799
apartment               1.447434   1.786772   2.232736   1.420717   1.775488   2.184830   1.683322   2.062110   3.223010
hauptgebaude            1.264359   2.767367   6.034419   2.744632   3.357431   4.362030   3.159510   5.015731   8.788682
wood_autumn             0.714002   1.666639   3.235271   2.984826   3.982941   5.385842   2.651131   3.686065   5.938165
wood_summer             0.691434   1.550447   3.067295   2.934619   3.729510   5.233264   1.978543   2.756018   3.536011
gazebo_summer           0.953463   2.060338   4.301263   2.730567   3.749908   5.229994   2.928825   4.369154   7.163291
gazebo_winter           0.674825   1.842922   4.479875   3.622142   4.781249   5.871060   3.045683   4.547794   7.173130
box_met                 7.793713   9.856043  13.366409   9.083450  13.985712  22.339738  12.956399  17.285173  28.753293
p2at_met                7.146841   9.213481  14.526304  10.667363  13.454345  21.274800  10.590098  16.306714  27.735237
planetary_map          28.932312  40.788811  67.322661  11.412726  15.999208  28.807680  42.374967  62.958295  99.798648
pioneer_slam            5.530644   7.984671  12.643310   2.789878   9.891751  16.956061   6.219392  11.736178  17.244092
pioneer_slam3           4.335621   6.041231   7.309748   4.381984   9.357496  13.582969   9.764630  13.510944  17.730549
long_office_household   3.491452   6.934493  11.313188   1.675962   3.546374  15.088290   2.358917   8.183446  18.018154
urban05                 1.695951   2.621079   4.606631   2.684101   4.037394   6.431827   3.354987   5.247426  12.041917
Total                   2.284029   6.114115  19.472148   3.357956   6.984476  16.655706   3.776988  10.053916  2

@fdila fdila closed this as completed Nov 2, 2023
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