This table lists the benchmark results for the 3D semantic label with limited annotations scenario.




Method Infoavg ioubathtubbedbookshelfcabinetchaircountercurtaindeskdoorfloorotherfurniturepicturerefrigeratorshower curtainsinksofatabletoiletwallwindow
sorted bysort bysort bysort bysort bysort bysort bysort bysort bysort bysort bysort bysort bysort bysort bysort bysort bysort bysort bysort bysort by
Q2E0.721 10.984 10.785 10.684 20.693 20.879 10.563 10.822 10.640 10.659 10.965 20.493 10.147 50.711 10.866 10.631 30.797 10.663 10.932 20.849 10.660 1
ActiveST0.703 20.977 20.776 30.657 50.707 10.874 20.541 20.744 20.605 20.610 20.968 10.442 40.126 60.705 20.785 20.742 10.791 20.586 20.940 10.839 20.645 2
Gengxin Liu, Oliver van Kaick, Hui Huang, Ruizhen Hu: Active Self-Training for Weakly Supervised 3D Scene Semantic Segmentation.
WS3D_LA_Sempermissive0.662 30.812 40.762 40.742 10.635 30.828 60.474 30.736 30.588 30.546 30.947 50.450 30.174 40.536 50.752 30.668 20.735 50.583 30.902 60.797 60.573 5
Kangcheng Liu: WS3D: Weakly Supervised 3D Scene Segmentation with Region-Level Boundary Awareness and Instance Discrimination. European Conference on Computer Vision (ECCV), 2022
DE-3DLearner LA0.639 40.839 30.723 60.681 30.629 40.839 50.424 40.728 40.538 50.526 40.945 60.427 60.120 70.511 70.643 60.547 60.781 30.566 50.905 40.809 50.607 4
Ping-Chung Yu, Cheng Sun, Min Sun: Data Efficient 3D Learner via Knowledge Transferred from 2D Model. ECCV 2022
GaIA0.638 50.536 120.783 20.651 60.600 50.840 30.413 50.728 40.490 70.520 60.948 40.475 20.299 10.518 60.680 40.629 40.729 60.573 40.906 30.815 40.626 3
Min Seok Lee*, Seok Woo Yang*, and Sung Won Han: GaIA: Graphical Information gain based Attention Network for Weakly Supervised 3D Point Cloud Semantic Segmentation. WACV 2023
LE0.608 60.791 50.726 50.651 60.589 60.779 90.346 90.662 80.493 60.524 50.923 130.430 50.234 30.572 30.638 70.411 100.708 70.533 80.855 70.782 70.508 7
One-Thing-One-Click0.594 70.756 60.722 70.494 120.546 80.795 70.371 60.725 60.559 40.488 70.957 30.367 80.261 20.547 40.575 120.225 120.671 100.543 60.904 50.826 30.557 6
Zhengzhe Liu, Xiaojuan Qi, Chi-Wing Fu: One Thing One Click: A Self-Training Approach for Weakly Supervised 3D Semantic Segmentation. CVPR 2021
VIBUSpermissive0.586 80.736 80.623 110.664 40.559 70.840 30.358 70.666 70.447 80.429 100.944 70.421 70.000 130.411 90.629 80.614 50.745 40.541 70.848 90.758 80.493 8
Beiwen Tian,Liyi Luo,Hao Zhao,Guyue Zhou: VIBUS: Data-efficient 3D Scene Parsing with VIewpoint Bottleneck and Uncertainty-Spectrum Modeling. ISPRS Journal of Photogrammetry and Remote Sensing
PointContrast_LA_SEM0.550 90.735 90.676 80.601 90.475 90.794 80.288 110.621 100.378 120.430 90.940 80.303 100.089 100.379 100.580 110.531 70.689 90.422 110.852 80.758 80.468 9
Viewpoint_BN_LA_AIR0.548 100.747 70.574 130.631 80.456 100.762 110.355 80.639 90.412 90.404 110.940 80.335 90.107 80.277 120.645 50.495 80.666 110.517 90.818 100.740 110.431 11
Liyi Luo, Beiwen Tian, Hao Zhao, Guyue Zhou: Pointly-supervised 3D Scene Parsing with Viewpoint Bottleneck.
CSC_LA_SEM0.531 110.659 100.638 100.578 100.417 110.775 100.254 120.537 110.396 100.439 80.939 100.284 120.083 110.414 80.599 100.488 90.698 80.444 100.785 110.747 100.440 10
SQN_LA0.486 120.587 110.649 90.527 110.372 120.718 120.320 100.510 120.393 110.325 120.924 120.290 110.095 90.287 110.607 90.356 110.626 120.416 120.672 120.680 130.359 12
Scratch_LA_SEM0.382 130.389 130.606 120.401 130.303 130.705 130.169 130.460 130.292 130.282 130.939 100.207 130.004 120.147 130.201 130.184 130.592 130.389 130.409 130.714 120.250 13


This table lists the benchmark results for the 3D semantic instance with limited annotations scenario.




Method Infoavg apbathtubbedbookshelfcabinetchaircountercurtaindeskdoorotherfurniturepicturerefrigeratorshower curtainsinksofatabletoiletwindow
sorted bysort bysort bysort bysort bysort bysort bysort bysort bysort bysort bysort bysort bysort bysort bysort bysort bysort bysort by
WS3D_LA_Inspermissive0.336 10.630 10.386 10.242 20.173 10.575 10.007 10.550 10.050 10.164 10.232 10.127 20.424 10.614 10.198 10.420 20.314 10.771 10.164 1
Kangcheng Liu: WS3D: Weakly Supervised 3D Scene Segmentation with Region-Level Boundary Awareness and Instance Discrimination. European Conference on Computer Vision (ECCV), 2022
Box2Mask_LA0.235 20.407 20.199 40.427 10.107 20.414 20.007 20.229 30.022 20.098 20.226 20.152 10.261 20.492 20.039 40.427 10.113 30.463 40.150 2
Julian Chibane, Francis Engelmann, Tuan Anh Tran, Gerard Pons-Moll: Box2Mask: Weakly Supervised 3D Semantic Instance Segmentation Using Bounding Boxes. ECCV 2022
CSC_LA_INS0.159 30.343 30.247 30.226 30.063 30.264 50.000 30.268 20.004 30.018 40.064 40.007 30.009 40.041 50.091 20.279 30.194 20.712 20.037 3
PointContrast_LA_INS0.124 40.037 50.109 50.085 40.052 40.287 30.000 30.219 40.001 40.040 30.104 30.002 40.074 30.211 30.055 30.239 40.036 50.661 30.020 4
Scratch_LA_INS0.089 50.306 40.319 20.025 50.035 50.274 40.000 30.157 50.001 50.006 50.031 50.000 50.000 50.095 40.017 50.172 50.077 40.094 50.002 5


This table lists the benchmark results for the 3D object detection with limited annotations scenario.




Method Infoavg ap 50%bathtubbedbookshelfcabinetchaircountercurtaindeskdoorotherfurniturepicturerefrigeratorshower curtainsinksofatabletoiletwindow
sorted bysort bysort bysort bysort bysort bysort bysort bysort bysort bysort bysort bysort bysort bysort bysort bysort bysort bysort by
WS3D_LA_ODpermissive0.341 11.000 10.629 10.426 10.070 10.608 10.063 10.176 10.503 10.132 10.084 10.001 10.337 10.220 10.103 10.628 10.282 10.739 10.131 1
Kangcheng Liu: WS3D: Weakly Supervised 3D Scene Segmentation with Region-Level Boundary Awareness and Instance Discrimination. European Conference on Computer Vision (ECCV), 2022
PointContrast_LA_DET0.135 20.667 20.296 30.145 20.002 30.330 30.000 40.000 30.050 30.049 20.023 20.000 30.002 40.006 40.034 30.472 20.052 20.285 40.011 2
CSC_LA_DET0.135 20.444 30.336 20.029 40.001 40.356 20.008 20.000 20.011 40.045 30.010 40.000 20.032 20.011 30.043 20.458 30.028 30.602 20.010 3
Scratch_LA_DET0.098 40.167 40.253 40.074 30.002 20.257 40.004 30.000 40.080 20.038 40.013 30.000 30.006 30.143 20.002 40.243 40.017 40.473 30.001 4


This table lists the benchmark results for the 3D semantic label with limited reconstructions scenario.




Method Infoavg ioubathtubbedbookshelfcabinetchaircountercurtaindeskdoorfloorotherfurniturepicturerefrigeratorshower curtainsinksofatabletoiletwallwindow
sorted bysort bysort bysort bysort bysort bysort bysort bysort bysort bysort bysort bysort bysort bysort bysort bysort bysort bysort bysort bysort by
WS3D_LR_Sem0.684 10.865 10.761 10.780 10.644 10.810 20.445 10.796 10.596 10.594 10.945 20.456 10.234 10.541 10.793 10.723 10.761 10.618 10.906 10.822 10.598 2
Kangcheng Liu: WS3D: Weakly Supervised 3D Scene Segmentation with Region-Level Boundary Awareness and Instance Discrimination. European Conference on Computer Vision (ECCV), 2022
NWSYY0.517 20.725 30.619 60.396 40.455 30.766 50.327 30.570 20.477 50.427 30.943 30.288 20.220 30.274 50.135 30.471 30.697 30.504 20.714 50.767 30.566 3
DE-3DLearner LR0.508 30.824 20.530 80.314 50.479 20.746 70.334 20.490 40.508 20.477 20.950 10.269 30.221 20.324 30.029 60.421 50.626 60.490 30.727 30.782 20.620 1
Ping-Chung Yu, Cheng Sun, Min Sun: Data Efficient 3D Learner via Knowledge Transferred from 2D Model. ECCV 2022
CSG_3DSegNet0.480 40.521 50.715 30.562 20.389 60.693 80.307 40.157 80.501 30.321 80.927 80.219 60.074 80.329 20.485 20.504 20.596 80.458 50.715 40.714 80.418 4
CSC_LR_SEM0.460 50.472 70.731 20.465 30.398 40.817 10.292 50.442 50.311 80.387 60.939 40.218 70.181 40.302 40.076 40.449 40.743 20.430 70.444 80.737 50.368 7
Viewpoint_BN_LR_AIR0.452 60.587 40.569 70.172 70.391 50.769 40.290 60.512 30.501 30.373 70.935 60.251 40.173 50.201 60.003 80.352 70.619 70.454 60.783 20.719 70.390 6
PointContrast_LR_SEM0.438 70.517 60.659 50.251 60.332 80.783 30.244 80.408 60.411 70.409 40.935 60.206 80.119 70.200 70.048 50.355 60.682 40.414 80.647 60.743 40.391 5
Scratch_LR_SEM0.401 80.240 80.674 40.095 80.347 70.763 60.271 70.204 70.449 60.406 50.936 50.220 50.127 60.199 80.004 70.348 80.665 50.477 40.493 70.730 60.366 8


This table lists the benchmark results for the 3D semantic instance with limited reconstructions scenario.




Method Infoavg apbathtubbedbookshelfcabinetchaircountercurtaindeskdoorotherfurniturepicturerefrigeratorshower curtainsinksofatabletoiletwindow
sorted bysort bysort bysort bysort bysort bysort bysort bysort bysort bysort bysort bysort bysort bysort bysort bysort bysort bysort by
WS3D_LR_Ins0.358 10.546 40.392 30.384 10.225 10.609 20.008 10.520 10.136 10.196 20.260 20.065 40.338 10.593 10.191 10.547 10.335 10.859 10.244 1
Kangcheng Liu: WS3D: Weakly Supervised 3D Scene Segmentation with Region-Level Boundary Awareness and Instance Discrimination. European Conference on Computer Vision (ECCV), 2022
InstTeacher3D0.310 20.741 10.407 20.173 20.164 20.675 10.000 40.249 30.061 20.308 10.340 10.336 10.206 20.000 30.160 30.441 20.318 20.821 20.179 2
Yizheng Wu, Zhiyu Pan, Kewei Wang, Xingyi Li, Jiahao Cui, Liwen Xiao, Guosheng Lin, Zhiguo Cao: Instance Consistency Regularization for Semi-Supervised 3D Instance Segmentation. IEEE Transactions on Pattern Analysis and Machine Intelligence
TWIST+CSC0.257 30.556 20.408 10.073 30.139 30.600 30.001 20.334 20.058 30.169 30.228 30.104 20.200 30.143 20.132 40.404 40.232 30.764 30.085 3
Ruihang Chu: TWIST: Two-Way Inter-label Self-Training for Semi-supervised 3D Instance Segmentation. CVPR 2022
CSC_LR_INS0.196 40.556 20.364 50.026 40.064 40.528 40.000 40.159 50.040 40.126 40.158 40.075 30.039 50.000 30.165 20.417 30.192 50.596 50.025 4
PointContrast_LR_INS0.176 50.444 60.375 40.001 60.057 60.465 60.000 40.234 40.021 60.092 60.137 50.035 60.004 60.000 30.079 50.391 50.204 40.620 40.016 6
Scratch_LR_INS0.156 60.481 50.279 60.023 50.061 50.499 50.001 30.001 60.025 50.114 50.108 60.055 50.047 40.000 30.023 60.325 60.176 60.568 60.018 5


This table lists the benchmark results for the 3D object detection with limited reconstructions scenario.




Method Infoavg ap 50%bathtubbedbookshelfcabinetchaircountercurtaindeskdoorotherfurniturepicturerefrigeratorshower curtainsinksofatabletoiletwindow
sorted bysort bysort bysort bysort bysort bysort bysort bysort bysort bysort bysort bysort bysort bysort bysort bysort bysort bysort by
WS3D_LR_ODpermissive0.374 10.867 10.797 10.655 10.104 10.678 10.046 10.215 10.406 10.186 10.219 10.034 10.354 10.160 10.101 10.741 10.306 10.679 10.181 1
Kangcheng Liu: WS3D: Weakly Supervised 3D Scene Segmentation with Region-Level Boundary Awareness and Instance Discrimination. European Conference on Computer Vision (ECCV), 2022
CSC_LR_DET0.191 20.667 20.468 30.226 20.036 20.420 30.025 20.010 30.081 30.066 30.045 20.000 20.162 30.010 30.017 20.657 20.109 20.420 30.013 2
PointContrast_LR_DET0.187 30.667 20.523 20.109 30.027 30.435 20.005 30.013 20.199 20.070 20.035 30.000 40.183 20.033 20.003 40.497 30.078 30.488 20.005 3
Scratch_LR_DET0.076 40.667 20.099 40.015 40.005 40.190 40.000 40.000 40.033 40.007 40.001 40.000 30.000 40.010 40.004 30.094 40.014 40.237 40.000 4