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Feb 22, 2024 · Announcing Stable Diffusion 3 in early preview, our most capable text-to-image model with greatly improved performance in multi-subject prompts, image quality, and spelling abilities.
New stable diffusion model (Stable Diffusion 2.0-v) at 768x768 resolution. Same number of parameters in the U-Net as 1.5, but uses OpenCLIP-ViT/H as the text encoder and is trained from scratch. SD 2.0-v is a so-called v-prediction model.
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Jun 1, 2024 · Stable Diffusion is a technique in the field of generative artificial intelligence (AI) that aims to generate high-quality images. It is an extension of diffusion probabilistic models, which are a class of generative models used for image generation.
Stable Diffusion is a latent text-to-image diffusion model capable of generating photo-realistic images given any text input, cultivates autonomous freedom to produce incredible imagery, empowers billions of people to create stunning art within seconds.
Stable Diffusion v1 refers to a specific configuration of the model architecture that uses a downsampling-factor 8 autoencoder with an 860M UNet and CLIP ViT-L/14 text encoder for the diffusion model.
Stable Diffusion is a text-to-image model that generates photo-realistic images given any text input. What makes Stable Diffusion unique ? It is completely open source.
Stable Diffusion is a Latent Diffusion model developed by researchers from the Machine Vision and Learning group at LMU Munich, a.k.a CompVis. Model checkpoints were publicly released at the end of August 2022 by a collaboration of Stability AI, CompVis, and Runway with support from EleutherAI and LAION.
Jul 10, 2024 · Stable Diffusion (SD) is a Generative AI model that uses latent diffusion to generate stunning images. This deep learning model can generate high-quality images from text descriptions, other images, and even more capabilities, revolutionizing the way artists and creators approach image creation. Despite its powerful capabilities, learning to use Stable Diffusion effectively can have a steep learning curve.
Jun 27, 2024 · In this paper, the impact of recursive inpainting is studied for one of the most widely used image models: Stable Diffusion. The results show that recursive inpainting can lead to image collapse, so ending with a nonmeaningful image, and that the outcome depends on several factors such as the type of image, the size of the inpainting masks, and ...
