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  2. Stable Diffusion - Wikipedia

    en.wikipedia.org/wiki/Stable_Diffusion

    Stable Diffusion is a deep learning, text-to-image model released in 2022 based on diffusion techniques. The generative artificial intelligence technology is the premier product of Stability AI and is considered to be a part of the ongoing artificial intelligence boom.

  3. Stability AI - Wikipedia

    en.wikipedia.org/wiki/Stability_AI

    Stability AI has made contributions to the field of generative AI, most notably through Stable Diffusion. This AI model allows images to be generated from textual descriptions. Beyond Stable Diffusion, Stability AI also develops Video, Audio, 3D, and text models. [19]

  4. Diffusion model - Wikipedia

    en.wikipedia.org/wiki/Diffusion_model

    Stable Diffusion 3 (2024-03) [66] changed the latent diffusion model from the UNet to a Transformer model, and so it is a DiT. It uses rectified flow. Stable Video 4D (2024-07) [67] is a latent diffusion model for videos of 3D objects.

  5. Alibaba to release open-source version of video generating AI ...

    www.aol.com/news/alibaba-release-open-source...

    Alibaba will release an open-source version of its video and image-generating artificial intelligence model, Wan 2.1, the Chinese tech giant said in a post on X on Tuesday. The company will give ...

  6. Flux (text-to-image model) - Wikipedia

    en.wikipedia.org/wiki/Flux_(text-to-image_model)

    Flux (also known as FLUX.1) is a text-to-image model developed by Black Forest Labs, based in Freiburg im Breisgau, Germany. Black Forest Labs were founded by former employees of Stability AI. As with other text-to-image models, Flux generates images from natural language descriptions, called prompts.

  7. Text-to-video model - Wikipedia

    en.wikipedia.org/wiki/Text-to-video_model

    By utilizing a pre-trained image diffusion model as a base generator, the model efficiently generated high-quality and coherent videos. Fine-tuning the pre-trained model on video data addressed the domain gap between image and video data, enhancing the model's ability to produce realistic and consistent video sequences. [14]

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