grad-cam generation

[jpainam]

Hi,
Could you share the util functions you used to generate the grad cam?

Thanks.

[kylemin]

Thank you for your interest.

We used the PyTorch version of Grad-CAM++: link. Please refer to this repository.
We also noticed that there is a well-maintained library for various types of CAMs that you can refer to: link2

Thank you,
Kyle

[jpainam]

Thank you.
I was able to generate GradCAM for model_base using [https://github.com/1Konny/gradcam_plus_plus-pytorch](this link).
For model_gaze, register_backward_hook doesn't fire. But register_forward_hook does.
So, I don't have the gradients['value']

Is there any else I'm missing?

You have three submodel (model_base, model_gaze, model_attn), when you said you visualize the last convolutional layer
of our model. Which of the three models?

Thank you

[kylemin]

You can visualize the output after the last conv layer (Mixed_5c) of model_base. You do not need to use register_backward_hook for model_gaze because you are expected to register the hooks only for model_base

[jpainam]

Ok thank. you train three differents network, (I3D, I3D w/ gaze and I3D w/ gaze and attention).
You visualize the output of Mixed_5c for each network.