DFFNet: An IoT-perceptive Dual Feature Fusion Network for General Real-time Semantic Segmentation

DFFNet

Paper

DFFNet: An IoT-perceptive Dual Feature Fusion Network for General Real-time Semantic Segmentation.

Xiangyan Tang, Wenxuan Tu, Keqiu Li, Jieren Cheng.

Information Sciences, 565: 326-343, 2021.

License

All rights reserved. Licensed under the Apache License 2.0

The code is released for academic research use only. For commercial use, please contact [[email protected]].

Installation

Clone this repo.

https://github.com/WxTu/DFFNet.git

• Windows or Linux
• Python3
• Pytorch(0.3+)
• Numpy
• Torchvision
• Matplotlib

Preparation

We use Cityscapes, Camvid and Helen datasets. To train a model on these datasets, download datasets from official websites.

Our backbone network is pre-trained on the ImageNet dataset provided by F. Li et al. You can download publically available pre-trained MobileNet v2 from this website.

Code Structure

• data/Dataset.py: processes the dataset before passing to the network.
• model/DFFNet.py: defines the architecture of the whole model.
• model/Backbone.py: defines the encoder.
• model/Layers.py: defines the MFFM, LSPM, and others.
• utils/Config.py: defines some hyper-parameters.
• utils/Process.py: defines the process of data pretreatment.
• utils/Utils.py: defines the loss, optimization, metrics, and others.
• utils/Visualization.py: defines the data visualization.
• Train.py: the entry point for training and validation.
• Test.py: the entry point for testing.

Visualization

Contact

[email protected]

Any discussions or concerns are welcomed!

Citation

If you use this code for your research, please cite our papers.

@article{Tang2021DFFNet,
  title={DFFNet: An IoT-perceptive Dual Feature Fusion Network for General Real-time Semantic Segmentation},
  author={Xiangyan Tang and Wenxuan Tu and Keqiu Li and Jieren Cheng},
  journal={Information Sciences},
  volume={565},
  pages={326-343},
  year={2021}
}

Acknowledgement

https://github.com/ansleliu/LightNet

https://github.com/meetshah1995/pytorch-semseg

https://github.com/zijundeng/pytorch-semantic-segmentation

https://github.com/Tramac/awesome-semantic-segmentation-pytorch