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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.
In December 2022, Midjourney was used to generate the images for an AI-generated children's book that was created over a weekend. Titled Alice and Sparkle, the book features a young girl who builds a robot that becomes self-aware. The creator, Ammaar Reeshi, used Midjourney to generate a large number of images, from which he chose 13 for the ...
CLIP is a separate model based on contrastive learning that was trained on 400 million pairs of images with text captions scraped from the Internet. Its role is to "understand and rank" DALL-E's output by predicting which caption from a list of 32,768 captions randomly selected from the dataset (of which one was the correct answer) is most ...
For example, a language model might assume that doctors and judges are male, and that secretaries or nurses are female, if those biases are common in the training data. [127] Similarly, an image model prompted with the text "a photo of a CEO" might disproportionately generate images of white male CEOs, [128] if
This is achieved by prompting the text encoder with class names and selecting the class whose embedding is closest to the image embedding. For example, to classify an image, they compared the embedding of the image with the embedding of the text "A photo of a {class}.", and the {class} that results in the highest dot product is outputted.
Example of an image made with VQGAN-CLIP (NightCafe Studio) Still from Eric Millikin's The Dance of the Nain Rouge, with subtitles. In the 2020s, text-to-image models, which generate images based on prompts, became widely used, marking yet another shift in the creation of AI generated artworks. [2]
The problem of content-based image retrieval is that of improving search results by taking into account visual information contained in the images themselves. Several CBIR methods make use of classifiers trained on image search results, to refine the search. In other words, object categorization from image search is one component of the system.
An example of user-generated content, a personalised sign and objects in the virtual world of Second Life. User-generated content (UGC), alternatively known as user-created content (UCC), emerged from the rise of intelligent web services which allow everyday users to create content, such as images, videos, audio, text, testimonials, and software (e.g. video game mods) and interact with other ...