Point Transformer

Benchmark Model Rank Results
3d-part-segmentation-on-shapenet-partPointTransformer#12Instance Average IoU: 86.6Class Average IoU: 83.7
3d-part-segmentation-on-shapenet-partPoint Transformer#31Instance Average IoU: 85.9
3d-point-cloud-classification-on-modelnet40PointTransformer#45Overall Accuracy: 93.7Mean Accuracy: 90.6
3d-point-cloud-classification-on-modelnet40Point Transformer#77Overall Accuracy: 92.8
3d-semantic-segmentation-on-s3disPointTransformer#4mIoU (Area-5): 70.4mIoU (6-Fold): 73.5
3d-semantic-segmentation-on-stpls3dPoint transformer#5mIOU: 47.64
point-cloud-segmentation-on-pointcloud-cPointTransformers#7mean Corruption Error (mCE): 1.049
semantic-segmentation-on-s3disPointTransformer#17Mean IoU: 73.5mAcc: 81.9oAcc: 90.2Number of params: 7.8M
semantic-segmentation-on-s3disKPConv#24Mean IoU: 70.6Number of params: 14.1MParams (M): 14.1
semantic-segmentation-on-s3disPointCNN#36Mean IoU: 65.4Number of params: N/A
semantic-segmentation-on-s3disSPGraph#41Mean IoU: 62.1Number of params: N/A
semantic-segmentation-on-s3disPointNet#50Mean IoU: 47.6Number of params: N/A
semantic-segmentation-on-s3dis-area5PointTransformer#26mIoU: 70.4mAcc: 76.5oAcc: 90.8Number of params: 7.8M
semantic-segmentation-on-s3dis-area5PointCNN#42mIoU: 57.3Number of params: N/A
semantic-segmentation-on-s3dis-area5PointNet#44mIoU: 41.1Number of params: N/A