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Text-MFF (Expert Systems With Applications, 2026):

权重和相关数据正在整理,预计一个月后将更新完毕所有内容。

欢迎参考和引用我们的工作(Welcome to refer to and cite our work)

文章发表在Expert Systems with Applications Volume 311, 15 May 2026上

Acknowledgments ※

训练、测试框架由 MFFT(EAAI, 2024) 构建而来。
网络结构由 ArtFlow(CVPR, 2021)Text-IF(CVPR, 2024) 启发而来。
感谢上述作者所作出的杰出工作。

The training and testing framework is built by MFFT(EAAI, 2024).
The network structure is inspired by ArtFlow(CVPR, 2021) and Text-IF(CVPR, 2024).
Thank you to all the authors mentioned above for their outstanding work.

My related work in MFF ※

Method Code Paper Status
MSI-DTrans (2024) GitHub Paper ✅ Published
FusionGCN (2025) GitHub Paper ✅ Published
Frame-MFF (N/A) GitHub (N/A) 🙅‍ Unrevealed
Text-MFF (2026) GitHub Paper ✅ Published

Future Prospects

  • The generation of statements is limited by a fixed vocabulary.
  • Only cosine similarity may mislead the network into producing incorrect statements.
  • Unable to effectively address strong and variable degradation interference.

How to use ※

  • 仅提供关键代码和权重。
  • 完整代码构建可参考FusionGCN项目。
  • 仅需简单替换即可完成。
  • Only provide key codes and weights.
  • The complete code construction can refer to the FusionGCN project.
  • Simply replace it to complete.

submitted and accepted dates

  • ESWA-D-25-15335: STJ(6.17)→WE(6.18)→UR(7.5)→DIP(9.15)→Revise(9.16)
  • R1: STJ(9.18)→WE(9.18)→UR(9.24)→DIP(10.6)→Revise(10.8)
  • R2: STJ(10.8)→WE(10.8)→UR(10.16)→DIP(12.24)→Revise(12.26)
  • R3: STJ(1.7)→WE(1.7)→UR(1.11)→DIP(1.14)→Revise(1.19)
  • R4: STJ(1.19)→WE(1.19)→UR(1.22)→DIP(1.26)→Acepted(1.26)

Reference information ※

@article{OUYANG2026131369,
title = {Text-MFF: Degradation multi-focus image fusion using multi expert text constraints},
journal = {Expert Systems with Applications},
volume = {311},
pages = {131369},
year = {2026},
issn = {0957-4174},
doi = {https://doi.org/10.1016/j.eswa.2026.131369}
}

Or

Ouyang Y, Zhai H, Jiang J, et al. Text-MFF: Degradation multi-focus image fusion using multi expert text constraints[J]. Expert Systems with Applications, 2026: 131369.

Contact information

E-mail addresses: 2023210516060@stu.cqnu.edu.cn (Y. Ouyang)

About

Official PyTorch implementation of “Text-MFF: Degradation multi-focus image fusion using multi expert text constraints”(ESWA, 2026)

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