Discriminator looses (?)

[SavvaI]

I am trying to apply cyclegan to my data, and at the beginning (1-2 epoch) it kinda makes needed transformation (with added noise), but then it just copies the image 2 times. Losses for G and D are near, so it seems that Generator is fooling discriminator with adversarial examples. I haven't find any solution, maybe someone have faced this problem? I have seen quite complex transformations with cyclegan, like face2food and face2doll

[junyanz]

For the complex transformation, I would recommend a small lambda_cycle (e.g. 1 or 2). Could you show some your results as well as loss plots? How big are your G and D losses?

[meeio]

@junyanz how much the lambda_cycle you use for horse2zebra?

[rohitsaluja22]

Hey @junyanz, this is Rohit. First, thanks for your code. It's really helpful.

I trained your model on around 1.5 k images at A and B sides. I am observing loss as attached image.

Do I expect Discriminators' errors to go to 0.5 ideally? If yes, should I train for more epochs or try changing lambda_cycle? Please suggest, how can I improve..