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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.
DALL-E 2's "inpainting" and "outpainting" use context from an image to fill in missing areas using a medium consistent with the original, following a given prompt. For example, this can be used to insert a new subject into an image, or expand an image beyond its original borders. [ 34 ]
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 ...
Re-captioning is used to augment training data, by using a video-to-text model to create detailed captions on videos. [7] OpenAI trained the model using publicly available videos as well as copyrighted videos licensed for the purpose, but did not reveal the number or the exact source of the videos. [5]
There are several architectures that have been used to create Text-to-Video models. Similar to Text-to-Image models, these models can be trained using Recurrent Neural Networks (RNNs) such as long short-term memory (LSTM) networks, which has been used for Pixel Transformation Models and Stochastic Video Generation Models, which aid in consistency and realism respectively. [31]
Firefly expanded its capabilities to Illustrator, Premiere Pro, and Express, particularly for generating photos, videos and audio to enhance or alter specific parts of the media. NVIDIA Picasso runs some Adobe Firefly models. [10] Google planned to use Firefly in Bard (now Gemini) as its AI image generator, but ended up using their own Imagen ...
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