Skip to content

SEG-GRAD-CAM: Interpretable Semantic Segmentation via Gradient-Weighted Class Activation Mapping

License

Notifications You must be signed in to change notification settings

kiraving/SegGradCAM

Folders and files

NameName
Last commit message
Last commit date

Latest commit

 

History

37 Commits
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 

Repository files navigation

SEG-GRAD-CAM

Publicly available implementation in Keras of our paper "Towards Interpretable Semantic Segmentation via Gradient-Weighted Class Activation Mapping" by Kira Vinogradova, Alexandr Dibrov, Gene Myers.

Check out our poster for a schematic overview of the method.

No updates or upgrades to newer versions are planned.

Installation

pip install git+https://github.com/kiraving/SegGradCAM.git

Requirements

Python 3.6, (recommended) Anaconda, versions of other packages can be found here

Please download Cityscapes (Fine annotations) if you intend to test Seg-Grad-CAM on a real-world dataset collected on German roads.

Usage

Credits:

CSBDeep

@article{weigert2018content,
  title={Content-aware image restoration: pushing the limits of fluorescence microscopy},
  author={Weigert, Martin and Schmidt, Uwe and Boothe, Tobias and M{\"u}ller, Andreas and Dibrov, Alexandr and Jain, Akanksha and Wilhelm, Benjamin and Schmidt, Deborah and Broaddus, Coleman and Culley, Si{\^a}n and others},
  journal={Nature methods},
  volume={15},
  number={12},
  pages={1090--1097},
  year={2018},
  publisher={Nature Publishing Group}
}

Cityscapes dataset:

@inproceedings{Cordts2016Cityscapes,
title={The Cityscapes Dataset for Semantic Urban Scene Understanding},
author={Cordts, Marius and Omran, Mohamed and Ramos, Sebastian and Rehfeld, Timo and Enzweiler, Markus and Benenson, Rodrigo and Franke, Uwe and Roth, Stefan and Schiele, Bernt},
booktitle={Proc. of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR)},
year={2016}
}

segmentation_models package:

 @misc{Yakubovskiy:2019,
    Author = {Pavel Yakubovskiy},
    Title = {Segmentation Models},
    Year = {2019},
    Publisher = {GitHub},
    Journal = {GitHub repository},
    Howpublished = {\url{https://github.com/qubvel/segmentation_models}}
  }

TextureMNIST dataset Code for toy dataset generation of "Grid Saliency for Context Explanations of Semantic Segmentation" paper

How to cite Seg-Grad-CAM:

@inproceedings{Vinogradova2020TowardsIS,
  title={Towards Interpretable Semantic Segmentation via Gradient-weighted Class Activation Mapping},
  author={Kira Vinogradova and Alexandr Dibrov and Eugene W. Myers},
  booktitle = {Proceedings of the AAAI Conference on Artificial Intelligence},
  year      = {2020},
  doi       = {10.1609/aaai.v34i10.7244}
}