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Found 2 papers, 1 papers with code
A Style-aware Discriminator for Controllable Image Translation
Current image-to-image translations do not control the output domain beyond the classes used during training, nor do they interpolate between different domains well, leading to implausible results.
Image Manipulation
Multimodal Unsupervised Image-To-Image Translation
+1
FA-GAN: Feature-Aware GAN for Text to Image Synthesis
Secondly, we introduce a feature-aware loss to provide the generator more direct supervision by employing the feature representation from the self-supervised discriminator.
