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EAT: Multi-Exposure Image Fusion with Adversarial Learning and Focal Transformer (IEEE TMM 2025)

This is the official implementation of the EAT model proposed in the paper (EAT: Multi-Exposure Image Fusion with Adversarial Learning and Focal Transformer) with Pytorch.

Requirements

  • Python 3
  • PyTorch 1.9.1
  • tqdm
  • pandas
  • joblib
  • matplotlib
  • timm

Cite the paper

If this work is helpful to you, please cite it as:

@ARTICLE{Tang_2025_EAT,
  author={Tang, Wei and He, Fazhi},
  journal={IEEE Transactions on Multimedia}, 
  title={EAT: Multi-Exposure Image Fusion with Adversarial Learning and Focal Transformer}, 
  year={2025},
  volume={},
  number={},
  pages={},
  doi={10.1109/TMM.2025.3535390}}

If you have any questions, feel free to contact me (weitang@tongji.edu.cn).

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[IEEE TMM 2025] Official implementation of EAT: Multi-Exposure Image Fusion with Adversarial Learning and Focal Transformer

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