DSS-pytorch
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Is there any code to distinguish foreground and background images?
As the author discribed in the chapter 4.5 in their TPAMI paper, they add another branch to do the classification for dataset including background images. But I am nor clear how they design the model so that for the bakcground images the gradients from the salient object detection module are not allowed to back-propagate. Is there any code related to this?