Unlike prior autoencoder-based diffusion models, Stable Diffusion incorporates a U-Net backbone with cross-attention layers to reduce noise while learning the latent representation. This enables the ...

The model encodes the semantic meaning of the prompt to guide the image generation process. Latent Space Representation: Stable Diffusion uses a Variational Autoencoder (VAE) to compress images ...

The variational autoencoder (VAE), which compresses source ... as well as the first to explore the new Stable Diffusion model for generating medical images. Admittedly, several limitations ...

Diffusion model training can generate dozens of training ... actual pixel space to speed up the image generation process. The autoencoder compresses the image into the latent space and applies ...

but the sequential prediction process is much faster than diffusion. These models use representations known as tokens to make predictions. An autoregressive model utilizes an autoencoder to ...

The base model of Stable Diffusion Excel, even without fine-tuning, has been producing impressive results. This has been made possible by the integration of Stable Diffusion Excel and the new ...

The architecture of Stable Audio consists of a variational autoencoder (VAE), a text encoder, and a U-Net-based conditioned diffusion model. The VAE plays a crucial role in compressing stereo ...