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As introduced in the paper, we want the Encoder to recover the latent vector from the output image in the cLR-GAN (Conditional Latent Regressor GAN). But we only update parameters in Generator. Why did you design the network like this ?
The text was updated successfully, but these errors were encountered:
We don't want the generator and encoder to cooperate and cheat. It is likely that the generator can produce a hidden signal and encoder can decode it. Therefore, we only update one network in the implementation. Encoder is still trained to reconstruct the photo in the cVAE-GAN branch.
As introduced in the paper, we want the Encoder to recover the latent vector from the output image in the cLR-GAN (Conditional Latent Regressor GAN). But we only update parameters in Generator. Why did you design the network like this ?
The text was updated successfully, but these errors were encountered: