BelHouse3D: A Dataset for 3D Indoor Scene Point Clouds
Description
The BelHouse3D dataset is a synthetic point cloud dataset for 3D indoor scene semantic segmentation. It is constructed using real-world references from 32 houses in Belgium, ensuring that the synthetic data closely aligns with real-world conditions. Additionally, it includes a test set with data occlusion to simulate out-of-distribution (OOD) scenarios, reflecting the occlusions commonly encountered in real-world point clouds. The dataset is used to benchmark both fully supervised and few-shot learning (FSL) segmentation models.
Resources
| Name |
Format |
Description |
Link |
Tags
- out-of-distribution-(ood)
- house-interior
- independent-and-identically-distributed-(iid)
- indoor-scene
- 3d-point-cloud
- semantic-segmentation
- few-shot-learning-(fsl)
- 3d-benchmark-dataset