Results for Sparse R-CNN
Submission data
| Full name | Sparse Convolutions for Semantic 3D Instance Segmentation |
| Description | Semantic Instance Segmentation based on Mask R-CNN, 3D-SIS and Submanifold Sparse Convolutional Networks |
| Input Data Types | Uses Color,Uses Geometry Uses 3D |
| Programming language(s) | Python 3.8, PyTorch 1.4 |
| Hardware | GeForce GTX 1080 Ti |
| Submission creation date | 16 Mar, 2020 |
| Last edited | 20 May, 2020 |
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 |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0.714 | 1.000 | 0.926 | 0.694 | 0.699 | 0.890 | 0.636 | 0.516 | 0.693 | 0.743 | 0.588 | 0.369 | 0.601 | 0.594 | 0.800 | 0.886 | 0.676 | 0.986 | 0.546 |