Thank you very much for your release. I have a question to ask. In the last dim of the network, you use an fc (feature_dim, class_dim) as the example to represent your theory in code. What if the conv operate (feature_dim, class_dim, kernel_size, kernel_size) has to be used in the specific task. If there would have any differences? because I was confused here whether we should consider the parameter of kernel or not. Meanwhile, the code would be changed.
is that right? NxW_ij = weight_m.expand(N,C,A) --》 NxW_ij = weight_m.expand(N,C,A,K,K)?
Dear author
Thank you very much for your release. I have a question to ask. In the last dim of the network, you use an fc (feature_dim, class_dim) as the example to represent your theory in code. What if the conv operate (feature_dim, class_dim, kernel_size, kernel_size) has to be used in the specific task. If there would have any differences? because I was confused here whether we should consider the parameter of kernel or not. Meanwhile, the code would be changed.
is that right? NxW_ij = weight_m.expand(N,C,A) --》 NxW_ij = weight_m.expand(N,C,A,K,K)?
Looking forward to your reply Best wishes