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LianYi233 / Trans-DAT

Y. Wu, L. Jiao, X. Liu, F. Liu, S. Yang and L. Li, Domain Adaptation-aware Transformer for Hyperspectral Object Tracking. IEEE Transactions on Circuits and Systems for Video Technology, 2024.
DOI: 10.1109/TCSVT.2024.3385273
MIT License
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domain-adaptation hyperspectral object-tracking

readme

Trans-DAT

This repository contains the official implementation for the following paper: Domain Adaptation-aware Transformer for Hyperspectral Object Tracking, which has been accepeted by IEEE TCSVT.

UPDATE

:star: Our tracking results (txt files) on HOT2023 datasets are available HERE. (Access Code: eugd)

:star: Our tracking results (txt files) on HOT2024 datasets are available HERE. (Access Code: 2024)

Environment

Dataset

In this paper, all the experimental results and comparisons are conducted on HOT2023 Challenge. The dataset could be downloaded from CONTEST PAGE. Please remember to modify the error annotations according to "Problems and Updates" before using the dataset.

Testing

cd pysot_toolkit
python test_3_dataset.py

Training

cd ltr
python run_training.py

Acknowledgement

The code in this repository is based on TransT. We would like to thank the authors for providing the great frameworks and models.

Citation

If you find our work useful in your research, please cite:

@ARTICLE{10491347,
  author={Wu, Yinan and Jiao, Licheng and Liu, Xu and Liu, Fang and Yang, Shuyuan and Li, Lingling},
  journal={IEEE Transactions on Circuits and Systems for Video Technology}, 
  title={Domain Adaptation-aware Transformer for Hyperspectral Object Tracking}, 
  year={2024},
  doi={10.1109/TCSVT.2024.3385273}}