Results for PointMTL
Submission data
| Full name | Multi-Transform Learning for Effective 3D Point Cloud Representations |
| Input Data Types | Uses Color Uses 3D |
| Programming language(s) | python with CUDA |
| Hardware | NVIDIA Tesla M40 and two E5-2650 CPUs |
| Submission creation date | 15 Jun, 2020 |
| Last edited | 15 Sep, 2020 |
3D semantic label results
| Info | avg iou | bathtub | bed | bookshelf | cabinet | chair | counter | curtain | desk | door | floor | otherfurniture | picture | refrigerator | shower curtain | sink | sofa | table | toilet | wall | window |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0.632 | 0.731 | 0.688 | 0.675 | 0.591 | 0.784 | 0.444 | 0.565 | 0.610 | 0.492 | 0.949 | 0.456 | 0.254 | 0.587 | 0.706 | 0.599 | 0.665 | 0.612 | 0.868 | 0.791 | 0.579 |