|
--- |
|
language: |
|
- "Python" |
|
thumbnail: "https://github.com/dvlab-research/FocalsConv" |
|
tags: |
|
- Sparse Conv |
|
- 3D Object Detection |
|
datasets: |
|
- KITTI |
|
- nuScenes |
|
--- |
|
|
|
[![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). |