VMA: Divide-and-Conquer Vectorized Map Annotation System for Large-Scale Driving Scene
ArXiv Preprint ([arXiv 2304.09807](https://arxiv.org/pdf/2304.09807.pdf))News
Aug. 30th, 2023: We release an initial version of VMA.Aug. 9th, 2023: Code will be released in around 3 weeks.
https://github.com/hustvl/VMA/assets/40697001/ec099b41-835a-409d-a007-9766c414a483
TL;DR VMA is a general map auto annotation framework based on MapTR, with high flexibility in terms of spatial scale and element type.
Getting Started
- Installation
- Prepare Dataset
- Inference on SD data (we only provide some samples of SD data for inference, since SD data is owned by Horizon)
- Train and Eval on NYC data
Auto Annotation Results
Remote sensing:
Urban scene:
Highway scene:
Citation
If you find VMA is useful in your research or applications, please consider giving us a star 🌟 and citing it by the following BibTeX entry.
@inproceedings{VMA,
title={VMA: Divide-and-Conquer Vectorized Map Annotation System for Large-Scale Driving Scene},
author={Chen, Shaoyu and Zhang, Yunchi and Liao, Bencheng, Xie, Jiafeng and Cheng, Tianheng and Sui, Wei and Zhang, Qian and Liu, Wenyu and Huang, Chang and Wang, Xinggang},
booktitle={arXiv preprint arXiv:2304.09807},
year={2023}
}