Here's a minimal example notebook that adds TAESD previewing to the 🧨 Diffusers implementation of SD2.1. TAESD is a tiny, distilled version of Stable Diffusion's VAE*, which consists of an encoder ...

To prevent the U-Net from losing important information while downsampling, short-cut connections are usually added between the downsampling ResNets of the encoder to the upsampling ResNets of the ...

Stable Diffusion can be used online for a fee and with content filters, or downloaded for free and used locally without content restrictions. Version 2.0 continues this open source approach. Leading ...

Researchers have been using AI models to decode information from ... visual brain regions to individual Stable Diffusion components. Specifically, the researchers map brain regions as inputs to image ...

Stable Diffusion ', which has become ... image information creator' and 'image decoder'. The main components are the ``text encoder (ClipText)'' that outputs the input text to 77 token embedding ...

One of the more powerful – and visually stunning – advances in generative AI has been the development of Stable Diffusion models. These models are used for image generation, image denoising, ...

but encoder and decoder dropping fail to achieve complete denoising. Originally designed for medical image segmentation, UNet has evolved, especially in 3D medical image segmentation. In text-to-image ...