Softmax GAN is a novel variant of Generative Adversarial Network (GAN). The key idea of Softmax GAN is to replace the classification loss in the original GAN with a softmax cross …

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Keras-GAN Collection of Keras implementations of Generative Adversarial Networks (GANs) suggested in research papers. These models are in some cases simplified versions of the …

Image-to-Image Translation in PyTorch. Contribute to junyanz/pytorch-CycleGAN-and-pix2pix development by creating an account on GitHub.

GAN Compression framework: ① Given a pre-trained teacher generator G', we distill a smaller “once-for-all” student generator G that contains all possible channel numbers through weight …

Implementation of 'lightweight' GAN proposed in ICLR 2021, in Pytorch. The main contributions of the paper is a skip-layer excitation in the generator, paired with autoencoding self-supervised …

This repository is the official implementation of MI-GAN. MI-GAN: A Simple Baseline for Image Inpainting on Mobile Devices Andranik Sargsyan, Shant Navasardyan, Xingqian Xu, …

May 18, 2024 · Generative adversarial networks (GAN) are a class of generative machine learning frameworks. A GAN consists of two competing neural networks, often termed the …

This paper introduces Diffusion-GAN that employs a Gaussian mixture distribution, defined over all the diffusion steps of a forward diffusion chain, to inject instance noise. A random sample …

StudioGAN provides implementations of 7 GAN architectures, 9 conditioning methods, 4 adversarial losses, 13 regularization modules, 3 differentiable augmentations, 8 evaluation …