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Found 8 papers, 2 papers with code
Logit As Auxiliary Weak-supervision for More Reliable and Accurate Prediction
When a person identifies objects, he or she can think by associating objects to many classes and conclude by taking inter-class relations into account.
GridMix: Strong regularization through local context mapping
Recently developed regularization techniques improve the networks generalization by only considering the global context.
Recycling the discriminator for improving the inference mapping of GAN
In order to analyze the real data in the latent space of GANs, it is necessary to investigate the inverse generation mapping from the data to the latent vector.
Editable Generative Adversarial Networks: Generating and Editing Faces Simultaneously
Also, we show that our model can achieve the competitive performance with the state-of-the-art attribute editing technique in terms of attribute editing quality.
Resembled Generative Adversarial Networks: Two Domains with Similar Attributes
We propose a novel algorithm, namely Resembled Generative Adversarial Networks (GAN), that generates two different domain data simultaneously where they resemble each other.
Discriminator Feature-based Inference by Recycling the Discriminator of GANs
Various studies assert that the latent space of a GAN is semanticallymeaningful and can be utilized for advanced data analysis and manipulation.
MGGAN: Solving Mode Collapse using Manifold Guided Training
Mode collapse is a critical problem in training generative adversarial networks.
Improved Training of Generative Adversarial Networks Using Representative Features
Because the AE learns to minimize forward KL divergence, our GAN training with representative features is influenced by both reverse and forward KL divergence.
