Awesome

SegMiF

Jinyuan Liu, Zhu Liu, Guanyao Wu, Long Ma, Risheng Liu, Wei Zhong, Zhongxuan Luo, Xin Fan*,“Multi-interactive Feature Learning and a Full-time Multi-modality Benchmark for Image Fusion and Segmentation”, International Conference on Computer Vision (ICCV), 2023. (Oral)

[ArXiv]

<h2> <p align="center"> FMB Dataset </p> </h2>

Preview

The preview of our FMB dataset is as follows.

preview

Download

<h2> <p align="center"> SegMiF Fusion </p> </h2>

Set Up on Your Own Machine

When you want to dive deeper or apply it on a larger scale, you can configure our SegMiF on your computer by following the steps below.

Virtual Environment

We strongly recommend that you use Conda as a package manager.

# create virtual environment
conda create -n SegMiF python=3.10
conda activate SegMiF
# select pytorch version yourself
# install SegMiF requirements
pip install -r requirements.txt

Data Preparation

Related data, checkpoint, and our results on MFNet Dataset can be downloaded in

[Google Drive]

Citation

If this work has been helpful to you, please feel free to cite our paper!

@inproceedings{liu2023segmif,
  title={Multi-interactive Feature Learning and a Full-time Multi-modality Benchmark for Image Fusion and Segmentation},
  author={Liu, Jinyuan and Liu, Zhu and Wu, Guanyao and Ma, Long and Liu, Risheng and Zhong, Wei and Luo, Zhongxuan and Fan, Xin},
  booktitle={International Conference on Computer Vision},
  year={2023}
}