yulongwang12 / visual-attribution Goto Github PK
View Code? Open in Web Editor NEWPytorch Implementation of recent visual attribution methods for model interpretability
License: BSD 2-Clause "Simplified" License
Pytorch Implementation of recent visual attribution methods for model interpretability
License: BSD 2-Clause "Simplified" License
The link to the weight is out of date
Hi Thank you for this contribution.
I am wondering if you have example code for how to apply this to classifiers that are not resnet-50, inception-v3, or vgg16? I am hoping to get excitation backprop figures for a 3 layer cnn and a 3 layer fully connected network.
Thanks for the great work!
Hi,
thanks for sharing this code!
Could you add some code for computing the patterns for PatternNet etc.? That would be very helpful.
Thanks,
Robin
Hi, @yulongwang12 ,
Our paper "LayerCAM: Exploring Hierarchical Class Activation Maps for Localization" is accepted by TIP recently, which can visualize the class activation maps from any CNN layer of an off-the-shelf network. Could you add our method to your popular repository for more people to try this method? Our method is a simple modification of Grad-CAM. It should easy to implement. Here is the paper and code. Hope for your reply.
Hi,
the download URL seems to have gone.
Is there a copy somewhere else?
Thank you!
Best regards
Thomas
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