zelaki/

eq-vae-ema-ldm

Arxiv: https://arxiv.org/abs/2502.09509

EQ-VAE regularizes the latent space of pretrained autoencoders by enforcing equivariance under scaling and rotation transformations.

This model is a regularized version of SD-VAE. We finetune it with EQ-VAE regularization for 44 epochs on Imagenet with EMA weights.

These weights are intended to be used with the EQ-VAE codebase or the CompVis Stable Diffusion codebase. If you are looking for the model to use with the 🧨 diffusers library, come here.

Reconstruction performance of eq-vae-ema on Imagenet Validation Set.