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Found 3 papers, 2 papers with code
Semantic Generative Augmentations for Few-Shot Counting
This requires to generate images that correspond to a given input number of objects.
Ranked #4 on
Object Counting
on FSC147
(using extra training data)
Wasserstein Loss for Semantic Editing in the Latent Space of GANs
The latent space of GANs contains rich semantics reflecting the training data.
Multi-Attribute Balanced Sampling for Disentangled GAN Controls
We propose to address disentanglement by subsampling the generated data to remove over-represented co-occuring attributes thus balancing the semantics of the dataset before training the classifiers.
