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.
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)
[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
Converts signals to images in real time using AI models
Pytorch implementation of BigGAN Generator with pretrained weights
Reimplementation of the Paper: Large Scale GAN Training for High Fidelity Natural Image Synthesis
Colabs for text prompt steered image generators
Multi-Variate Temporal GAN for Large Scale Video Generation
To associate your repository with the biggan topic, visit your repo's landing page and select "manage topics."