Comments (4)
Hi, during training, we use a soft activation map (1-pk) to mask out background regions, i.e., (1-pk) * x. With the L_BTM loss, pk will be optimized to only activate the background regions.
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Hi, during training, we use a soft activation map (1-pk) to mask out background regions, i.e., (1-pk) * x. With the L_BTM loss, pk will be optimized to only activate the background regions.
Ok,thank you! The specific approach is to generate the initial CAMs p, and then use this (1-p) to multiply with image x to mask out the foreground object. From the perspective of the image matrix, this make the pixel value of the foreground object smaller and the pixel value of the background larger to mask out the foreground object, right? Is there any deficiency in my understanding of this?
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Exactly. p should be normalized into [0,1] by sigmoid.
Btw, welcome to star CLIMS. :)
from clims.
Exactly. p should be normalized into [0,1] by sigmoid. Btw, welcome to star CLIMS. :)
Thank you! I have starred CLIMS.
from clims.
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