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Thank you for your interesting papers and sharing the code.
I have a question about the paper, in particular the simplified NL module.
If I understand well, you are using the self attention in order to get some features which will permits you , then to weighted the different channel of your input images right ?
So if I want to code it from your code it will give :
context = self.spatial_pool(x) # dim context: NxCx1x1
output = conv2D(context) # conv1x1 with C input channels and C output channels , dim output NxCx1x1
return x + output
is that right ?
The text was updated successfully, but these errors were encountered:
Hi,
Thank you for your interesting papers and sharing the code.
I have a question about the paper, in particular the simplified NL module.
If I understand well, you are using the self attention in order to get some features which will permits you , then to weighted the different channel of your input images right ?
So if I want to code it from your code it will give :
is that right ?
The text was updated successfully, but these errors were encountered: