Searching Efficient 3D Architectures with Sparse Point-Voxel Convolution

Benchmark Model Rank Results
robust-3d-semantic-segmentation-on-robo3dSPVCNN-34#1mean Corruption Error (mCE): 99.16%
robust-3d-semantic-segmentation-on-robo3dSPVCNN-18#4mean Corruption Error (mCE): 100.30%
3d-semantic-segmentation-on-wildscenesSPVCNN#2mIoU: 36.78
robust-3d-semantic-segmentation-on-wod-cSPVCNN-34#2mean Corruption Error (mCE): 98.72%
robust-3d-semantic-segmentation-on-wod-cSPVCNN-18#4mean Corruption Error (mCE): 103.60%
robust-3d-semantic-segmentation-on-nuscenes-cSPVCNN-34#3mean Corruption Error (mCE): 97.45%
robust-3d-semantic-segmentation-on-nuscenes-cSPVCNN-18#7mean Corruption Error (mCE): 106.65%
lidar-semantic-segmentation-on-nuscenesSPVCNN++#9test mIoU: 0.811
lidar-semantic-segmentation-on-nuscenesSPVNAS#13test mIoU: 0.77
3d-semantic-segmentation-on-semantickittiSPVNAS#15test mIoU: 66.4%val mIoU: 64.7%