zelaki/eq-vae-ema

EQ-VAE: Equivariance Regularized Latent Space for Improved Generative Image Modeling

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

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

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Model Description

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

Model Usage

2. Loading the Model
   You can load the model from the Hugging Face Hub:

   from transformers import AutoencoderKL
   model = AutoencoderKL.from_pretrained("zelaki/eq-vae-ema")
   

Metrics

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

Metric	Score
FID	0.552
PSNR	26.158
LPIPS	0.133
SSIM	0.725

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