iamzihan/RWKVFusionDataset

RWKVFusion [TPAMI 2025]

<div align="center"> <a href=https://scholar.google.com/citations?user=pv61pEAAAAJ&hl=en> Zihan Cao </a> | <a href=https://scholar.google.com/citations?user=E5KO9XsAAAAJ&hl=en> Yu-Jie Liang </a> | <a href=https://scholar.google.com/citations?user=TZs9NxkAAAAJ&hl=en> Liang-Jian Deng </a> | <a href=https://scholar.google.com/citations?user=sjbuAMAAAAJ&hl=en> Gemine Vivone</>

<a>University of Electronic Science and Technology of China (UESTC) </a><br> <a>Institute of Methodologies for Environmental Analysis, CNR-IMAA </a> </div>

Official pre-processed dataset of Unify language and mask guidance in an efficient network (TPAMI).

This dataset contains general image fusion task:

• —Pansharpening: WV3, GF2, QB (Raw dataset at Pan-Collection).
• —Hyperspectral and multispectral image fusion: Cheikusei, Pavia (Raw dataset at PSRT).
• —Multi-exposure image fusion: MEFB, SICE.
• —Multi-focus image fusion: RealMFF, WHU-WFI, Lytro.

If you find this work useful, please kindly cite our paper:

@ARTICLE{RWKVFusion,
  author={Cao, Zi-Han and Liang, Yu-Jie and Deng, Liang-Jian and Vivone, Gemine},
  journal={IEEE Transactions on Pattern Analysis and Machine Intelligence},
  title={An Efficient Image Fusion Network Exploiting Unifying Language and Mask Guidance},
  year={2025},
  volume={},
  number={},
  pages={1-18},
  doi={10.1109/TPAMI.2025.3591930}
}

If you have any questions, please contact me: iamzihan666@gmail.com