I train the DSS models, and test it. when i test it, i found that: the saliency object boundary have too much noise. do u have the same problem? maybe the reason is that: the code use mean to fuse, while the paper use a conv layer to fuse.
i will try it later.
This is caused by “inference” (the z_fuse achieve here is a little different),the paper use z_fuse, z_2, z_3, z_4. You can see the output of demo (s-out6 and fusion without blur boundary)
Current results is based on average fusion stragedy, I will train a learnable fusion soon(the paper using learnable way)
I train the DSS models, and test it. when i test it, i found that: the saliency object boundary have too much noise. do u have the same problem? maybe the reason is that: the code use mean to fuse, while the paper use a conv layer to fuse. i will try it later.