SceneNN is an RGB-D scene dataset consisting of more than 100 indoor scenes. The scenes are captured at various places, e.g., offices, dormitory, classrooms, pantry, etc., from University of Massachusetts Boston and Singapore University of Technology and Design.
All scenes are reconstructed into triangle meshes and have per-vertex and per-pixel annotation. The dataset is additionally enriched with fine-grained information such as axis-aligned bounding boxes, oriented bounding boxes, and object poses.
Source: SceneNN: A Scene Meshes Dataset with aNNotations
Image Source: http://103.24.77.34/scenenn/home/
Variants: SceneNN
This dataset is used in 1 benchmark:
| Task | Model | Paper | Date |
|---|---|---|---|
| 3D Instance Segmentation | OccuSeg | OccuSeg: Occupancy-aware 3D Instance Segmentation | 2020-03-14 |
| 3D Instance Segmentation | MLS-CRF | JSIS3D: Joint Semantic-Instance Segmentation of … | 2019-04-01 |
| 3D Instance Segmentation | MT-PNet | JSIS3D: Joint Semantic-Instance Segmentation of … | 2019-04-01 |
Recent papers with results on this dataset: