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  2. Text-to-image model - Wikipedia

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

    An image conditioned on the prompt an astronaut riding a horse, by Hiroshige, generated by Stable Diffusion 3.5, a large-scale text-to-image model first released in 2022. A text-to-image model is a machine learning model which takes an input natural language description and produces an image matching that description.

  3. Image registration - Wikipedia

    en.wikipedia.org/wiki/Image_registration

    Image registration or image alignment algorithms can be classified into intensity-based and feature-based. [3] One of the images is referred to as the moving or source and the others are referred to as the target, fixed or sensed images.

  4. Google Brain - Wikipedia

    en.wikipedia.org/wiki/Google_Brain

    Example of an image generated by Imagen 3.0. Google Brain announced in 2022 that it created two different types of text-to-image models called Imagen and Parti that compete with OpenAI's DALL-E. [36] [37] Later in 2022, the project was extended to text-to-video. [38] Imagen development was transferred to Google Deepmind after the merger with ...

  5. Stable Diffusion - Wikipedia

    en.wikipedia.org/wiki/Stable_Diffusion

    A "hypernetwork" is a small pretrained neural network that is applied to various points within a larger neural network, and refers to the technique created by NovelAI developer Kurumuz in 2021, originally intended for text-generation transformer models. Hypernetworks steer results towards a particular direction, allowing Stable Diffusion-based ...

  6. Adobe Firefly - Wikipedia

    en.wikipedia.org/wiki/Adobe_Firefly

    Adobe Firefly is a generative machine learning text-to-image model included as part of Adobe Creative Cloud.It is currently being tested in an open beta phase. [1] [2] [3]Adobe Firefly is developed using Adobe's Sensei platform.

  7. DALL-E - Wikipedia

    en.wikipedia.org/wiki/DALL-E

    DALL-E has three components: a discrete VAE, an autoregressive decoder-only Transformer (12 billion parameters) similar to GPT-3, and a CLIP pair of image encoder and text encoder. [22] The discrete VAE can convert an image to a sequence of tokens, and conversely, convert a sequence of tokens back to an image.