This repository contains the official PyTorch implementation of our paper:
Our codebase is built upon the BEVDet (v1) and StreamPETR codebases. Please refer to their original repos for instractions about setting up datsets and environments.
@inproceedings{yang2024widthformer,
title={Widthformer: Toward efficient transformer-based bev view transformation},
author={Yang, Chenhongyi and Lin, Tianwei and Huang, Lichao and Crowley, Elliot J},
booktitle={2024 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)},
pages={8457--8464},
year={2024},
organization={IEEE}
}