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FocalsConv
Yukang/FocalsConv
FocalsConv is a machine learning model from Yukang. Use it for the machine learning task on the model card, and read the license before you ship it in a product.
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Updated May 30, 2022
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At a glance
- Access
- Public
- Created
- May 28, 2022
- Updated
- May 30, 2022
- SHA
- 24ef770c
Model card
From the Hugging Face model README
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] [Github] <br /> Yukang Chen, Yanwei Li, Xiangyu Zhang, Jian Sun, Jiaya Jia<br />
KITTI dataset
| Car@R11 | Car@R40 | download | |
|---|---|---|---|
| PV-RCNN + Focals Conv | 83.91 | 85.20 | Google | Baidu (key: m15b) |
| PV-RCNN + Focals Conv (multimodal) | 84.58 | 85.34 | Google | Baidu (key: ie6n) |
| Voxel R-CNN (Car) + Focals Conv (multimodal) | 85.68 | 86.00 | Google | Baidu (key: tnw9) |
nuScenes dataset
| mAP | NDS | download | |
|---|---|---|---|
| CenterPoint + Focals Conv (multi-modal) | 63.86 | 69.41 | Google | Baidu (key: 01jh) |
| CenterPoint + Focals Conv (multi-modal) - 1/4 data | 62.15 | 67.45 | Google | Baidu (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.
- Created
- May 28, 2022
- Updated
- May 30, 2022