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Found 10 papers, 7 papers with code
StyleGAN-V: A Continuous Video Generator with the Price, Image Quality and Perks of StyleGAN2
We build our model on top of StyleGAN2 and it is just ${\approx}5\%$ more expensive to train at the same resolution while achieving almost the same image quality.
HyperCGAN: Text-to-Image Synthesis with HyperNet-Modulated Conditional Generative Adversarial Networks
To the best of our knowledge, our work is the first one which explores text-controllable continuous image generation.
Imaginative Walks: Generative Random Walk Deviation Loss for Improved Unseen Learning Representation
By generating representations of unseen classes based on their semantic descriptions, e. g., attributes or text, generative ZSL attempts to differentiate unseen from seen categories.
Aligning Latent and Image Spaces to Connect the Unconnectable
In this work, we develop a method to generate infinite high-resolution images with diverse and complex content.
Ranked #1 on
Infinite Image Generation
on LHQ
Class Normalization for Zero-Shot Learning
Normalization techniques have proved to be a crucial ingredient of successful training in a traditional supervised learning regime.
Interpolating Points on a Non-Uniform Grid using a Mixture of Gaussians
In this work, we propose an approach to perform non-uniform image interpolation based on a Gaussian Mixture Model.
Adversarial Generation of Continuous Images
In most existing learning systems, images are typically viewed as 2D pixel arrays.
Ranked #7 on
Image Generation
on FFHQ 256 x 256
Class Normalization for (Continual)? Generalized Zero-Shot Learning
Normalization techniques have proved to be a crucial ingredient of successful training in a traditional supervised learning regime.
Loss Landscape Sightseeing with Multi-Point Optimization
We present multi-point optimization: an optimization technique that allows to train several models simultaneously without the need to keep the parameters of each one individually.
