Current diffusion models require many steps to generate a sample, limiting their speed and use in real-time applications.

conda install pytorch torchvision -c pytorch pip install transformers==4.19.2 diffusers invisible-watermark pip install -e . Stable Diffusion v1 refers to a specific configuration of the model ...

As with other machine-learning models, diffusion models work by sampling large amounts of data ... That reduction in steps, they note, has drastically reduced the amount of time their model takes to ...

OpenAI is pushing the boundaries of AI-generated image and video creation. Now, media generation happens in a flash, making ...

making real-time generative AI applications much more feasible. Reaching diffusion-model quality with far less computational resources The team behind sCM trained a continuous-time consistency ...

As with other machine-learning models, diffusion models work by sampling ... has drastically reduced the amount of time their ...

In this work, we propose a framework based on wavelet transform and diffusion model, which is called DiffWT. Different from previous approaches, our method employs a discrete wavelet transform (DWT) ...

“After listening to the valuable community feedback, instead of a quick fix, we took the time to further develop a version that advances our mission ... Image: Stability AI Another important aspect of ...

This model can fill in missing frames in videos, turn a single image into a moving scene, and even extend a short clip by ...

It suggests that this model class could have similar scaling potential to large language models. Until now, autoregressive models—the standard for language models—were considered less powerful than ...

Abstract: Advanced diffusion models (DMs) perform impressively in image super-resolution (SR), but the high memory and computational costs hinder their deployment. Binarization, an ultra-compression ...