---
license: mit
library_name: pytorch
tags:
- lidar
- point-cloud
- point-cloud-completion
- scene-completion
- 3d
- semantickitti
- autonomous-driving
- pytorch_model_hub_mixin
- model_hub_mixin
---

# RapidLiDAR

Single-pass LiDAR scene completion trained on SemanticKITTI.

Code, installation, and full documentation: [https://github.com/AzharSindhi/RapidLiDAR](https://github.com/AzharSindhi/RapidLiDAR)

Arxiv: [http://arxiv.org/abs/2608.16490](http://arxiv.org/abs/2608.16490)

## Usage

```python
from rapidlidar.models.hub import RapidLiDARHubModel

model = RapidLiDARHubModel.from_pretrained("Azhar88/RapidLiDAR-coarse")
model.eval()

# x_partial: (B, N, 3) partial point cloud
output = model(x_partial, up_factor=10)
completed_points = output.points  # (B, N * up_factor, 3)
```