Computation question

[jczh98]

Origin paper mention that CX(X, X) = 1 while CX(X,Y) = 1/N if X is far from Y.
So contextual loss is zero when two images are equal and large when two images are dissimilarity.
I found that your code which computes equation (1) uses 1 - CX and I'm confused with this and its result.
I wish your help, thanks.

[S-aiueo32]

@neverfelly
Thank you for your pointing. I agree with your interpretation of CX.
I don't remember why the inversion was placed in the line...
Anyway, according to https://gist.github.com/yunjey/3105146c736f9c1055463c33b4c989da, I'm sure that it was my fault.

On the current master branch, it has been fixed.
If you confirm it or have the other questions, please post here.

[jczh98]

Thanks for your great contribution to the contextual loss package.
Also, I found a problem with contextual bilateral loss, the original implementation uses MSE distance instead of L1 distance.

[S-aiueo32]

CoBi is still under developing because of the OOM during L2 distance computation.
I could test it only with L1 so I selected L1 for the computation of spatial loss to keep consistency in the test.

The intrinsic solution is to avoid the OOM but I don't have any idea for memory-efficient computation now.