I have written the files demo.m and generate_bbox.m in Python in order to be able to use the script without Matlab. In order to run it in Python one just need to run

python py_generate_bbox.py

We propose a simple technique to expose the implicit attention of Convolutional Neural Networks on the image. It highlights the most informative image regions relevant to the predicted class. You could get attention-based model instantly by tweaking your own CNN a little bit more. The paper is published at CVPR'16.

git clone https://github.com/metalbubble/CAM.git
cd CAM

The demo video of what the CNN is looking is here. The reimplementation in tensorflow is here.

@inproceedings{zhou2016cvpr,
    author    = {Zhou, Bolei and Khosla, Aditya and Lapedriza, Agata and Oliva, Aude and Torralba, Antonio},
    title     = {Learning Deep Features for Discriminative Localization},
    booktitle = {Computer Vision and Pattern Recognition},
    year      = {2016}
}

The pre-trained models and the CAM technique are released for unrestricted use.