README.md

---
language: code
tags:
- Sparse Conv
- 3D Object Detection
datasets:
- KITTI
- nuScenes
thumbnail: https://github.com/dvlab-research/FocalsConv
---

[![arXiv](https://img.shields.io/badge/arXiv-Paper-<COLOR>.svg)](https://arxiv.org/abs/2204.12463)

# Focal Sparse Convolutional Networks for 3D Object Detection (CVPR 2022, Oral)

This is the official implementation of ***Focals Conv*** (CVPR 2022), a new sparse convolution design for 3D object detection (feasible for both lidar-only and multi-modal settings). For more details, please refer to:

**Focal Sparse Convolutional Networks for 3D Object Detection [[Paper](https://arxiv.org/abs/2204.12463)] [[Github](https://github.com/dvlab-research/FocalsConv)]** <br />
Yukang Chen, Yanwei Li, Xiangyu Zhang, Jian Sun, Jiaya Jia<br />

#### KITTI dataset
|                                             | Car@R11 | Car@R40  |download | 
|---------------------------------------------|-------:|:-------:|:---------:|
| [PV-RCNN + Focals Conv](OpenPCDet/tools/cfgs/kitti_models/pv_rcnn_focal_lidar.yaml) | 83.91 | 85.20 | [Google](https://drive.google.com/file/d/1XOpIzHKtkEj9BNrQR6VYADO_T5yaOiJq/view?usp=sharing) \| [Baidu](https://pan.baidu.com/s/1t1Gk8bDv8Q_Dd5vB4VtChA) (key: m15b) |
| [PV-RCNN + Focals Conv (multimodal)](OpenPCDet/tools/cfgs/kitti_models/pv_rcnn_focal_multimodal.yaml) | 84.58 | 85.34 | [Google](https://drive.google.com/file/d/183araPcEmYSlruife2nszKeJv1KH2spg/view?usp=sharing) \| [Baidu](https://pan.baidu.com/s/10XodrSazMFDFnTRdKIfbKA) (key: ie6n) |
| [Voxel R-CNN (Car) + Focals Conv (multimodal)](OpenPCDet/tools/cfgs/kitti_models/voxel_rcnn_car_focal_multimodal.yaml) | 85.68 | 86.00 | [Google](https://drive.google.com/file/d/1M7IUosz4q4qHKEZeRLIIBQ6Wj1-0Wjdg/view?usp=sharing) \| [Baidu](https://pan.baidu.com/s/1bIN3zDmPXrURMOPg7pukzA) (key: tnw9) |


#### nuScenes dataset
|                                             | mAP | NDS | download | 
|---------------------------------------------|----------:|:-------:|:---------:|
| [CenterPoint + Focals Conv (multi-modal)](CenterPoint/configs/nusc/voxelnet/nusc_centerpoint_voxelnet_0075voxel_fix_bn_z_focal_multimodal.py) | 63.86	| 69.41	 | [Google](https://drive.google.com/file/d/12VXMl6RQcz87OWPxXJsB_Nb0MdimsTiG/view?usp=sharing) \| [Baidu](https://pan.baidu.com/s/1ZXn-fhmeL6AsveV2G3n5Jg) (key: 01jh) | 
| [CenterPoint + Focals Conv (multi-modal) - 1/4 data](CenterPoint/configs/nusc/voxelnet/nusc_centerpoint_voxelnet_0075voxel_fix_bn_z_focal_multimodal_1_4_data.py) | 62.15	| 67.45	 | [Google](https://drive.google.com/file/d/1HC3nTEE8GVhInquwRd9hRJPSsZZylR58/view?usp=sharing) \| [Baidu](https://pan.baidu.com/s/1tKlO4GgzjXojzjzpoJY_Ng) (key: 6qsc) | 


## Citation 
If you find this project useful in your research, please consider citing:

```
@inproceedings{focalsconv-chen,
  title={Focal Sparse Convolutional Networks for 3D Object Detection},
  author={Chen, Yukang and Li, Yanwei and Zhang, Xiangyu and Sun, Jian and Jia, Jiaya},
  booktitle={Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition},
  year={2022}
}
```

## License

This project is released under the [Apache 2.0 license](LICENSE).