| ## EQ-VAE: Equivariance Regularized Latent Space for Improved Generative Image Modeling | |
| Arxiv: https://arxiv.org/abs/2502.09509 <br> | |
| **EQ-VAE** regularizes the latent space of pretrained autoencoders by enforcing equivariance under scaling and rotation transformations. | |
| --- | |
| #### Model Description | |
| This model is a regularized version of [SD-VAE](https://github.com/CompVis/latent-diffusion). We finetune it with EQ-VAE regularization for 44 epochs on Imagenet with EMA weights. | |
| ## Model Usage | |
| These weights are intended to be used with the [EQ-VAE codebase](https://github.com/zelaki/eqvae) or the [CompVis Stable Diffusion codebase](https://github.com/CompVis/stable-diffusion). | |
| If you are looking for the model to use with the 🧨 diffusers library, [come here](https://huggingface.co/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 | | |
| --- | |