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 |
Last uploaded | 16 Mar, 2020 |
3D semantic instance results
Info | avg ap | bathtub | bed | bookshelf | cabinet | chair | counter | curtain | desk | door | otherfurniture | picture | refrigerator | shower curtain | sink | sofa | table | toilet | window |
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
0.292 | 0.704 | 0.213 | 0.153 | 0.154 | 0.551 | 0.053 | 0.212 | 0.132 | 0.174 | 0.274 | 0.070 | 0.363 | 0.441 | 0.176 | 0.424 | 0.234 | 0.758 | 0.161 |