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[IROS 2024 Oral Presentation] WidthFormer: Toward Efficient Transformer-based BEV View Transformation

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WidthFormer: Toward Efficient Transformer-based BEV View Transformation

This repository contains the official PyTorch implementation of our paper:

WidthFormer: Toward Efficient Transformer-based BEV View Transformation. Chenhongyi Yang, Tianwei Lin, Lichao Huang, Elliot J. Crowley, Arxiv 2401.03836

Usage

Environment Setup

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.

Citation

@article{yang2024widthformer,
  title={WidthFormer: Toward Efficient Transformer-based BEV View Transformation},
  author={Yang, Chenhongyi and Lin, Tianwei and Huang, Lichao and Crowley, Elliot J},
  journal={arXiv preprint arXiv:2401.03836},
  year={2024}
}

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[IROS 2024 Oral Presentation] WidthFormer: Toward Efficient Transformer-based BEV View Transformation

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