sankin97/logonet

LoGoNet

[CVPR2023] LoGoNet: Towards Accurate 3D Object Detection with Local-to-Global Cross-Modal Fusion

Code is released at https://github.com/PJLab-ADG/LoGoNet.

Citation

If you find our paper useful, please kindly cite us via:

@inproceedings{logonet,
  title={LoGoNet: Towards Accurate 3D Object Detection with Local-to-Global Cross-Modal Fusion},
  author={Xin Li and Tao Ma and Yuenan Hou and Botian Shi and Yuchen Yang and Youquan Liu and Xingjiao Wu and Qin Chen and Yikang Li and Yu Qiao and Liang He},
  booktitle = {Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2023}
}

logonet's Issues

Publication time

Hi, thanks for your excellent work, can I know the release date please? I would like to thank you for your hard work! I wish you success in your research!

precision on kitti test set

Thank you for sharing this project！I have a issue to ask you:
I try to train LoGoNet with all KITTI training data for 80 epochs and submit results to KITTI test set. But the precision of car on moderate level is only 82%, I want to know how to achieve 85.06% as paper said?

Is the model configuration on kitti test set different from that on kitti validation set?

If so, what changes need to be made?