A Collection of Variational Autoencoders (VAE) in PyTorch.

Source code for "Taming Visually Guided Sound Generation" (Oral at the BMVC 2021)

A toolkit for non-parallel voice conversion based on vector-quantized variational autoencoder

Torchélie is a set of utility functions, layers, losses, models, trainers and other things for PyTorch.

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

VQ-VAE/GAN implementation in pytorch-lightning

Experimental implementation for a sparse-dictionary based version of the VQ-VAE2 paper

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

implementation of VQVAE in pytorch

Applying multiple VQ along the feature axis

[GDSC Solution Challenge] Facegram All-Part Merged Repository