VQ-VAE-2
VQ-VAE-2
**VQ-VAE-2** is a type of variational autoencoder that combines a a two-level hierarchical VQ-[VAE](https://paperswithcode.com/method/vae) with a self-attention autoregressive model ([PixelCNN](https://paperswithcode.com/method/pixelcnn)) as a prior. The encoder and decoder architectures are kept simple and light-weight as in the original [VQ-VAE](https://paperswithcode.com/method/vq-vae), with the only difference that hierarchical multi-scale latent maps are used for increased resolution.
Generating Diverse High-Fidelity Images with VQ-VAE-2
https://paperswithcode.com/paper/190600446
Generating Diverse High-Fidelity Images with VQ-VAE-2