Great Work! I read your paper and realize your goal is to optimize three networks G, D, and R through L1loss(you named correction loss), SMloss, and adversarial loss.
But there is one thing in the test phase that confuses me. Which of G(x) and R(G(x)) should I use as the final generated image? I noticed a test phase in your code that only use G(x) as the final translated image. Is it correct for Reg-GAN that use G(x) rather than R(G(x)) as the translated image?
If there is some mistake in my understanding of RegGAN, hope you can point it out.
Great Work! I read your paper and realize your goal is to optimize three networks G, D, and R through L1loss(you named correction loss), SMloss, and adversarial loss.
But there is one thing in the test phase that confuses me. Which of G(x) and R(G(x)) should I use as the final generated image? I noticed a test phase in your code that only use G(x) as the final translated image. Is it correct for Reg-GAN that use G(x) rather than R(G(x)) as the translated image?
If there is some mistake in my understanding of RegGAN, hope you can point it out.