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  2. StyleGAN - Wikipedia

    en.wikipedia.org/wiki/StyleGAN

    Just after, the GAN game consists of the pair (() +), (() +) generating and discriminating 8x8 images. Here, the functions u , d {\displaystyle u,d} are image up- and down-sampling functions, and α {\displaystyle \alpha } is a blend-in factor (much like an alpha in image composing) that smoothly glides from 0 to 1.

  3. 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.

  4. Generative adversarial network - Wikipedia

    en.wikipedia.org/wiki/Generative_adversarial_network

    For example, for generating images that look like ImageNet, the generator should be able to generate a picture of cat when given the class label "cat". In the original paper, [ 1 ] the authors noted that GAN can be trivially extended to conditional GAN by providing the labels to both the generator and the discriminator.

  5. Rendering (computer graphics) - Wikipedia

    en.wikipedia.org/wiki/Rendering_(computer_graphics)

    An image rendered using POV-Ray 3.6 An architectural visualization rendered in multiple styles using Blender. Rendering is the process of generating a photorealistic or non-photorealistic image from input data such as 3D models.

  6. DALL-E - Wikipedia

    en.wikipedia.org/wiki/DALL-E

    DALL-E was revealed by OpenAI in a blog post on 5 January 2021, and uses a version of GPT-3 [5] modified to generate images.. On 6 April 2022, OpenAI announced DALL-E 2, a successor designed to generate more realistic images at higher resolutions that "can combine concepts, attributes, and styles". [6]

  7. Computer-generated imagery - Wikipedia

    en.wikipedia.org/wiki/Computer-generated_imagery

    A computer-generated image featuring a house at sunset, made in Blender. Modern architects use services from computer graphic firms to create 3-dimensional models for both customers and builders. These computer generated models can be more accurate than traditional drawings.

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  9. Deep learning super sampling - Wikipedia

    en.wikipedia.org/wiki/Deep_learning_super_sampling

    The second stage is an image upscaling step which uses the single raw, low-resolution frame to upscale the image to the desired output resolution. Using just a single frame for upscaling means the neural network itself must generate a large amount of new information to produce the high resolution output, this can result in slight hallucinations ...