Results for SAT
Submission data
| Full name | Size-Aware Transformer for 3D Point Cloud Semantic Segmentation |
| Input Data Types | Uses Color,Uses Geometry Uses 3D |
| Programming language(s) | Python with CUDA |
| Hardware | RTX 3090 24 G |
| Submission creation date | 16 Oct, 2022 |
| Last edited | 4 Jan, 2023 |
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 |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0.742 | 0.860 | 0.765 | 0.819 | 0.769 | 0.848 | 0.533 | 0.829 | 0.663 | 0.631 | 0.955 | 0.586 | 0.274 | 0.753 | 0.896 | 0.729 | 0.760 | 0.666 | 0.921 | 0.855 | 0.733 |