This application trains a model to reverse the process of adding Gaussian noise to images — essentially learning how to start from noise and create realistic outputs. Inspired by DDPMs like DALL·E 2 ...

A team of Japanese researchers led by Yu Takagi and Shinji Nishimoto from Osaka University’s Graduate School of Frontier Biosciences used Stable Diffusion AI to help generate images based on ...

Last week, Swiss software engineer Matthias Bühlmann discovered that the popular image synthesis model Stable Diffusion could compress existing bitmapped images with fewer visual artifacts than ...

Inpaint_images: contains the original images, masked images, as well as the inpainted images based on the RePaint pipeline implemented in pipelines.py. Since our analysis was based on the Linear and ...

To do this, the model is trained, like a diffusion model, to observe the image destruction process, but learns to take an image at any level of obscuration (i.e. with a little information missing ...

The modified diffusion model is able to address this problem, it add input anchor image’s latent at the beginning of inferencing rather than Gaussian random latent as input. Hence, we focus on ...

• Last but not least, Stable Diffusion refers to the whole domain of text-to-image landscape. The poster children of the text-to-image landscape—Dall-E2, MidJourney, Imagen, etc.—are closed ...

An image generated by Stable Diffusion XL 1.0. Image Credits: Stability AI “We hope that by releasing this much more powerful open source model, the resolution of the images will not be the only ...

Stable Diffusion 3, the next generation of the popular open source AI image generation model has been unveiled by StabilityAI and it is an impressive leap forward. Details of the new model were ...