Skip to content
New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

About the Class Activation Maps(CAM) in your paper #5

Open
eveleslie opened this issue Nov 11, 2022 · 1 comment
Open

About the Class Activation Maps(CAM) in your paper #5

eveleslie opened this issue Nov 11, 2022 · 1 comment

Comments

@eveleslie
Copy link

Hello, I am glad to see your open-source code. Your work inspires me a lot. I want to ask how the class activation diagram in the paper is drawn. Because I know that the class activation map function provided in Torchcam allows only one input, while few-shot work often has multiple inputs.
How do you handle this, and is it convenient to provide the code for me to learn?
I am looking forward to your reply!

@wangxiang1230
Copy link
Contributor

Hello, I am glad to see your open-source code. Your work inspires me a lot. I want to ask how the class activation diagram in the paper is drawn. Because I know that the class activation map function provided in Torchcam allows only one input, while few-shot work often has multiple inputs. How do you handle this, and is it convenient to provide the code for me to learn? I am looking forward to your reply!

Hi, thanks for you attention. For class activation map, we input an episodic task to the model. Note that the support and query videos need to be entered into ResNet-50 together when visualizing (i.e. support and query are concatenated and then entered into the network), rather than separately. Once the loss has been calculated, the Grad-CAM visualization can be done in a similar way to the common image. Sorry that code cannot be shared at this time as a very complex open source approval process is required. Thanks again.

Sign up for free to join this conversation on GitHub. Already have an account? Sign in to comment
Labels
None yet
Projects
None yet
Development

No branches or pull requests

2 participants