[Xuan Xiong](), Yicheng Liu, [Tianyuan Yuan](), Yue Wang, Yilun Wang, Hang Zhao*
A neural representation of HD maps to improve local map inference performance for autonomous driving.
This repo is the official implementation of "Neural Map Prior for Autonomous Driving"(CVPR 2023). Our main contributions are:
Notes
project/neural_map_prior/map_tiles/lane_render.py
.tools/data_sampler.py
.We experiment with BEVFormer, lift-spat-shoot, HDMapNet and VectorMapNet architectures on nuScenes.
Model Config | Modality | Divider | Crossing | Boundary | All(mIoU) | Checkpoint Link |
---|---|---|---|---|---|---|
BEVFormer | Camera | 49.20 | 28.67 | 50.43 | 42.76 | model |
BEVFormer + NMP | Camera | 54.20 | 34.52 | 56.94 | 48.55 | model |
Please check installation for installation and data_preparation for preparing the nuScenes dataset.
Please check getting_started for training, evaluation, and visualization of neural_map_prior.
Any questions or suggestions are welcome!
We would like to thank all who contributed to the open-source projects listed below. Our project would be impossible to get done without the inspiration of these outstanding researchers and developers.
The designate project/neural_map_prior
as a module is inspired by the implementations
of DETR3D.
If you find neural_map_prior useful in your research or applications, please consider citing:
@inproceedings{xiong2023neuralmapprior,
author = {Xiong, Xuan and Liu, Yicheng and Yuan, Tianyuan and Wang, Yue and Wang, Yilun and Zhao Hang},
title = {Neural Map Prior for Autonomous Driving},
journal = {Proceedings of the IEEE/CVF International Conference on Computer Vision (CVPR)},
year = {2023}
}
This project is licensed under the Apache 2.0 license.