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-entropy loss in 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 from the …

Code for NeurIPS 2024 paper - The GAN is dead; long live the GAN! A Modern Baseline GAN - by Huang et al. - brownvc/R3GAN

Simple Implementation of many GAN models with PyTorch. - Yangyangii/GAN-Tutorial

The Progressive GAN code repository contains a command-line tool for recreating bit-exact replicas of the datasets that we used in the paper. The tool also provides various utilities for operating on the …

Curated list of awesome GAN applications and demo. Contribute to nashory/gans-awesome-applications development by creating an account on GitHub.

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 Discriminator …

Wasserstein GAN stabilize the training by using Wasserstein-1 distance GAN before using JS divergence has the problem of non-overlapping, leading to mode collapse and convergence difficulty. …

Apr 12, 2023 · 做 GAN 有一段时间了，可以回答下这个问题。 G是你的任务核心，最后推理用的也是G，所以G的LOSS是要下降收敛接近0的，G的目标是要欺骗到D。 而成功的训练中，由于要达到G …

Official TP-GAN Tensorflow implementation for the ICCV17 paper "Beyond Face Rotation: Global and Local Perception GAN for Photorealistic and Identity Preserving Frontal View Synthesis" by Huang, …