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During training, at first only , are used in a GAN game to generate 4x4 images. Then G N − 1 , D N − 1 {\displaystyle G_{N-1},D_{N-1}} are added to reach the second stage of GAN game, to generate 8x8 images, and so on, until we reach a GAN game to generate 1024x1024 images.
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.
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.
Similarly, an image model prompted with the text "a photo of a CEO" might disproportionately generate images of white male CEOs, [128] if trained on a racially biased data set. A number of methods for mitigating bias have been attempted, such as altering input prompts [ 129 ] and reweighting training data.
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.
[2] [3] [4] The concept was created for a website from the MIT Media Lab in 2020, where users could create ganimal images. [5] 78,210 ganimals were generated from hybrid pairs of animal labels from BigGAN (G1) and 3,058,362,945 ganimals generated from blending G1 ganimals. [3] The term ganimal is a portmanteau between the words GAN and animal ...
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The Stable Diffusion model supports the ability to generate new images from scratch through the use of a text prompt describing elements to be included or omitted from the output. [8] Existing images can be re-drawn by the model to incorporate new elements described by a text prompt (a process known as "guided image synthesis" [ 49 ] ) through ...