There are 5 repositories under vqgan topic.
[NeurIPS 2022] Towards Robust Blind Face Restoration with Codebook Lookup Transformer
Pytorch implementation of Make-A-Scene: Scene-Based Text-to-Image Generation with Human Priors
[CVPR 2023] | RIDCP: Revitalizing Real Image Dehazing via High-Quality Codebook Priors
Feed forward VQGAN-CLIP model, where the goal is to eliminate the need for optimizing the latent space of VQGAN for each input prompt
Implements VQGAN+CLIP for image and video generation, and style transfers, based on text and image prompts. Emphasis on ease-of-use, documentation, and smooth video creation.
Start here
Zero-Shot Text-to-Image Generation VQGAN+CLIP Dockerized
NTIRE 2022 - Image Inpainting Challenge
Implementation of Binary Latent Diffusion
Streamlit Tutorial (ex: stock price dashboard, cartoon-stylegan, vqgan-clip, stylemixing, styleclip, sefa)
VQ-VAE/GAN implementation in pytorch-lightning
Traditional deepdream with VQGAN+CLIP and optical flow. Ready to use in Google Colab.
Implementation of Taming Transformers for High-Resolution Image Synthesis (https://arxiv.org/abs/2012.09841) in PyTorch
Docker for VQGAN+CLIP (z+quantize method)
Colabs for text prompt steered image generators
An unofficial PyTorch implementation of VQGAN
Text-to-Image Synthesis using Multimodal (VQGAN + CLIP) Architectures
VQGAN from LDM without hell of dependencies
VQGAN and CLIP are actually two separate machine learning algorithms that can be used together to generate images based on a text prompt. VQGAN is a generative adversarial neural network that is good at generating images that look similar to others (but not from a prompt), and CLIP is another neural network that is able to determine how well a caption (or prompt) matches an image.
Vector-Quantized Generative Adversarial Networks
Pytorch implementation of "Taming transformer for high resolution image synthesis (VQGAN)"
Pipeline to create Paper2Fig dataset, a dataset for text-to-image generation from research papers and figures (e.g., diagrams of architectures or methods in fields like Machine Learning or Computer Vision)
yet another VQGAN-CLIP variation
Experiments with Baudelaire and a text-to-image GAN.
Implementing MaskGIT for image inpainting with PyTorch