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  2. Generative adversarial network - Wikipedia

    en.wikipedia.org/wiki/Generative_adversarial_network

    The generator is decomposed into a pyramid of generators =, with the lowest one generating the image () at the lowest resolution, then the generated image is scaled up to (()), and fed to the next level to generate an image (+ (())) at a higher resolution, and so on. The discriminator is decomposed into a pyramid as well.

  3. Generative artificial intelligence - Wikipedia

    en.wikipedia.org/wiki/Generative_artificial...

    Generative AI systems trained on sets of images with text captions include Imagen, DALL-E, Midjourney, Adobe Firefly, FLUX.1, Stable Diffusion and others (see Artificial intelligence art, Generative art, and Synthetic media). They are commonly used for text-to-image generation and neural style transfer. [66]

  4. 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.

  5. StyleGAN - Wikipedia

    en.wikipedia.org/wiki/StyleGAN

    Progressive GAN [9] is a method for training GAN for large-scale image generation stably, by growing a GAN generator from small to large scale in a pyramidal fashion. Like SinGAN, it decomposes the generator as =, and the discriminator as =.

  6. Fréchet inception distance - Wikipedia

    en.wikipedia.org/wiki/Fréchet_inception_distance

    The Fréchet inception distance (FID) is a metric used to assess the quality of images created by a generative model, like a generative adversarial network (GAN) [1] or a diffusion model. [2] [3] The FID compares the distribution of generated images with the distribution of a set of real images (a "ground truth" set).

  7. Vision transformer - Wikipedia

    en.wikipedia.org/wiki/Vision_transformer

    ViT had been used for image generation as backbones for GAN [43] and for diffusion models (diffusion transformer, or DiT). [44] DINO [26] has been demonstrated to learn useful representations for clustering images and exploring morphological profiles on biological datasets, such as images generated with the Cell Painting assay. [45]

  8. Prompt engineering - Wikipedia

    en.wikipedia.org/wiki/Prompt_engineering

    Example of prompt engineering for text-to-image generation, with Fooocus In 2022, text-to-image models like DALL-E 2 , Stable Diffusion , and Midjourney were released to the public. [ 48 ] These models take text prompts as input and use them to generate AI-generated images .

  9. Inception score - Wikipedia

    en.wikipedia.org/wiki/Inception_score

    The Inception Score (IS) is an algorithm used to assess the quality of images created by a generative image model such as a generative adversarial network (GAN). [1] The score is calculated based on the output of a separate, pretrained Inception v3 image classification model applied to a sample of (typically around 30,000) images generated by the generative model.