Results for GraphCut
Submission data
| Full name | Learning Superpoint Graph Cut for 3D Instance Segmentation |
| Input Data Types | Uses Color,Uses Geometry Uses 3D |
| Programming language(s) | python, c++, cuda |
| Hardware | TITAN RTX, Core i5, 24GB Memory |
| Submission creation date | 17 May, 2022 |
| Last edited | 19 May, 2022 |
3D semantic instance results
| Info | avg ap 25% | bathtub | bed | bookshelf | cabinet | chair | counter | curtain | desk | door | otherfurniture | picture | refrigerator | shower curtain | sink | sofa | table | toilet | window |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0.832 | 1.000 | 0.922 | 0.724 | 0.798 | 0.902 | 0.701 | 0.856 | 0.859 | 0.715 | 0.706 | 0.748 | 0.640 | 1.000 | 0.934 | 0.862 | 0.880 | 1.000 | 0.729 |