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TAME

This is the repository for "TAME: Temporal Audio-based Mamba for Enhanced Drone Trajectory Estimation and Classification".

Installation

$ conda create -n your_env_name python=3.10.13
$ pip install torch==2.1.1 torchvision==0.16.1 torchaudio==2.1.1 --index-url https://download.pytorch.org/whl/cu118
$ pip install -r requirement.txt
$ pip install causal_conv1d==1.1.0
$ cd kernels/selective_scan
$ pip install .
$ cd ..
$ cd ..
$ pip install .

Data

The dataset comes from the CVPR UG2+ challenge. For details, please see MMAUD. The data used in the paper is processed and segmented data, which can be downloaded from Baidu Cloud. For audio segmentation, please refer to this link.

Overview

Experiment

Acknowledgement

This project is based on Mamba (paper, code), VMamba (paper, code). Thanks for their wonderful works.

Citation

If you find Vim is useful in your research or applications, please consider giving us a star 🌟 and citing it by the following BibTeX entry.

@inproceedings{xiao2024tametemporalaudiobasedmamba,
      title={TAME: Temporal Audio-based Mamba for Enhanced Drone Trajectory Estimation and Classification}, 
      author={Zhenyuan Xiao and Huanran Hu and Guili Xu and Junwei He},
      year={2025/5},
      eprint={2412.13037},
      archivePrefix={arXiv},
      primaryClass={cs.SD},
      url={https://arxiv.org/abs/2412.13037}, 
      booktitle={IEEE International Conference on Acoustics, Speech and Signal Processing}
}