pytorch-CycleGAN-and-pix2pix
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rec_B works well, fake_B works poorly, identity 0.5, lambda_A, and lambda_B 10
rec_B works well, fake_B works poorly, identity 0.5, lambda_A, and lambda_B 10
Could you share more details?
Using a paired dataset, training the recurrent network was found to be very close rec_B to the real_B, and the fake_B was much different from both rec_B and real_B