A Collection of Variational Autoencoders (VAE) in PyTorch.
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Updated
May 6, 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
Language Quantized AutoEncoders
SignAvatars: A Large-scale 3D Sign Language Holistic Motion Dataset and Benchmark
Voice conversion (VC) investigation using three variants of VAE
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
Tensorflow Implementation of "Theory and Experiments on Vector Quantized Autoencoders"
Image Generation using VQVAE and GPT Models
VQGAN from LDM without hell of dependencies
implementation of VQVAE in pytorch
Applying multiple VQ along the feature axis
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