StudioGAN is a Pytorch library providing implementations of representative Generative Adversarial Networks (GANs) for conditional/unconditional image generation.

The author's officially unofficial PyTorch BigGAN implementation.

🦋A PyTorch implementation of BigGAN with pretrained weights and conversion scripts.

Pytorch implementation of LARGE SCALE GAN TRAINING FOR HIGH FIDELITY NATURAL IMAGE SYNTHESIS (BigGAN)

Programming assignments and quizzes from all courses within the GANs specialization offered by deeplearning.ai

Official Implementation of the paper "A U-Net Based Discriminator for Generative Adversarial Networks" (CVPR 2020)

Code for: Transforming and Projecting Images into Class-conditional Generative Networks

[CVPR 2022] Unsupervised Image-to-Image Translation with Generative Prior

Official implementation of FQ-GAN

Generate Amazing Anime Pictures With BigGAN. Just Have Fun !!!

BigGAN; Knowledge Distillation; Black-Box; Fast Training; 16x compression

Data Augmentation optimized for GAN

Create music videos using CLIP with BigGAN, DALL-E and StyleGAN

Pytorch implementation of BigGAN Generator with pretrained weights

MichelAI, video clip creator based on BigGAN

Reimplementation of the Paper: Large Scale GAN Training for High Fidelity Natural Image Synthesis

The Wandering Dreamer: An Synthetic Feedback Loop

Multi-Variate Temporal GAN for Large Scale Video Generation

Colabs for text prompt steered image generators

Using Deep Learning to create fake images of games using PyTorch