Hello, I don't have a pure math background and I've tried to make my own naive implemenation of DIM where the "discriminator" is just a standard binary crossentropy sigmoid classifier where there is a 50% chance the input is global and and + example and a 50% chance the input is a global and - sample. Is this vanilla classification scheme a correct implementation of the project?
Yeh, it's just binary classification between pairs (global, local that comes from same image that produced global) and (global, local that comes from probably different image that that that produced global).
Hello, I don't have a pure math background and I've tried to make my own naive implemenation of DIM where the "discriminator" is just a standard binary crossentropy sigmoid classifier where there is a 50% chance the input is global and and + example and a 50% chance the input is a global and - sample. Is this vanilla classification scheme a correct implementation of the project?