A Collection of Variational Autoencoders (VAE) in PyTorch.
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Updated
Jun 13, 2024 - Python
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
Fast and scalable search of whole-slide images via self-supervised deep learning - Nature Biomedical Engineering
Demo of robust semantic communication against semantic noise
Experimental implementation for a sparse-dictionary based version of the VQ-VAE2 paper
Voice conversion (VC) investigation using three variants of VAE
Inverse DALL-E for Optical Character Recognition
Language Quantized AutoEncoders
OmniTokenizer: one model and one weight for image-video joint tokenization.
Tensorflow Implementation of "Theory and Experiments on Vector Quantized Autoencoders"
VQ-VAE/GAN implementation in pytorch-lightning
Large-Scale Bidirectional Training for Zero-Shot Image Captioning
Applying multiple VQ along the feature axis
Image Generation using VQVAE and GPT Models
implementation of VQVAE in pytorch
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