---
license: apache-2.0
library_name: torch-pointcloud
tags:
- point-cloud
- 3d
- pytorch
- torch-pointcloud
- pointrcnn
- object-detection
datasets:
- kitti
model-index:
- name: pointrcnn.kitti.openpcdet
  results:
  - task:
      type: 3d-object-detection
    dataset:
      name: KITTI
      type: kitti
    metrics:
    - name: mAP
      type: map
      value: 69.29
---

# Model card for pointrcnn.kitti.openpcdet

A PointRCNN 3D object detection model (two-stage point-based proposal and refinement). Trained on KITTI.

## Model Details

- **Model Type:** 3D object detection
- **Model Stats:**
  - Params (M): 4.0
  - Input channels: 4
  - Classes: 3
  - Features: 128
- **Dataset:** KITTI
- **Metrics:** mAP 69.29 (reference 68.41)
- **Paper:** [PointRCNN: 3D Object Proposal Generation and Detection from Point Cloud](https://arxiv.org/abs/1812.04244)
- **Converted from:** [open-mmlab/OpenPCDet](https://github.com/open-mmlab/OpenPCDet) (Apache-2.0)
- **Library:** [torch-pointcloud](https://github.com/arthurdjn/pytorch-pointcloud)

## Install

```bash
pip install torch-pointcloud
```

## Usage

```python
import torch
import torch_pointcloud as tp
from torch_pointcloud.utils.data import collate

model, info = tp.create_model(
    "pointrcnn.kitti.openpcdet",
    task="detection",
    pretrained=True,
    return_info=True,
)
model = model.eval()

# synthetic sample with the keys a dataset provides
num_points = 8192
sample = {
    "pos": torch.randn(num_points, 3),
    "intensity": torch.rand(num_points, 1),
}
data = info["transform"](sample)
data = collate([data])

with torch.no_grad():
    out = model(data.get("x"), data["pos"], data["batch"])
```

## Feature extraction

```python
with torch.no_grad():
    features = model.forward_features(data.get("x"), data["pos"], data["batch"])  # 128 channels
```

## Citation

```bibtex
@inproceedings{shi2019pointrcnn,
  title   = {PointRCNN: 3D Object Proposal Generation and Detection from Point Cloud},
  author  = {Shaoshuai Shi and Xiaogang Wang and Hongsheng Li},
  booktitle = {CVPR},
  year    = {2019}
}

@inproceedings{geiger2012kitti,
  title     = {Are we ready for Autonomous Driving? The {KITTI} Vision Benchmark Suite},
  author    = {Geiger, Andreas and Lenz, Philip and Urtasun, Raquel},
  booktitle = {CVPR},
  year      = {2012}
}

@software{dujardin2026pytorchpointcloud,
  author  = {Arthur Dujardin},
  title   = {PyTorch PointCloud},
  year    = {2026},
  doi     = {10.5281/zenodo.22159632},
  url     = {https://github.com/arthurdjn/pytorch-pointcloud},
}
```