There are 1 repository under vqvae topic.
A Collection of Variational Autoencoders (VAE) in PyTorch.
A toolkit for non-parallel voice conversion based on vector-quantized variational autoencoder
Fast and scalable search of whole-slide images via self-supervised deep learning - Nature Biomedical Engineering
Language Quantized AutoEncoders
Voice conversion (VC) investigation using three variants of VAE
SignAvatars: A Large-scale 3D Sign Language Holistic Motion Dataset and Benchmark
Demo of robust semantic communication against semantic noise
Inverse DALL-E for Optical Character Recognition
Experimental implementation for a sparse-dictionary based version of the VQ-VAE2 paper
VQ-VAE/GAN implementation in pytorch-lightning
Large-Scale Bidirectional Training for Zero-Shot Image Captioning
This repo implements VQVAE on mnist and as well as colored version of mnist images. It also implements simple LSTM for generating sample numbers using the encoder outputs of trained VQVAE
Tensorflow Implementation of "Theory and Experiments on Vector Quantized Autoencoders"
VQGAN from LDM without hell of dependencies
Image Generation using VQVAE and GPT Models
Official code for the NeurIPS 2022 paper "Posterior Matching for Arbitrary Conditioning".
implementation of VQVAE in pytorch
State of the art of generative models and in-depth study of diffusion models
An educational project dedicated to text-to-image generation with neural networks. VQVAE and BPE autoencoders are used to learn the embedding of text and image respectively. A transformer-based model then is trained to predict the next token in the concatenated sequence of image and text tokens and used for generation.
Implementation of basic autoencodeur, VAE and VQVAE in Flax
Compression via Vector Quantization in PyTorch
Improving Semantic Control in Discrete Latent Spaces with Transformer Quantized Variational Autoencoders