Imagen (text-to-image model)
Image-generating machine learning model From Wikipedia, the free encyclopedia
Imagen, Imagen 2, and Imagen 3 are text-to-image models developed by Google DeepMind. They were developed by Google Brain until the company's merger with DeepMind in April 2023.[1] Imagen is primarily used to generate images from text prompts, similar to Stability AI's Stable Diffusion, OpenAI's DALL-E, or Midjourney.
.jpg) An image generated with Imagen 3. Partial prompt: Softly illuminated afternoon valley with meandering river | |
| Developer(s) | Google DeepMind |
|---|---|
| Stable release | Imagen 3
/ 13 August 2024 |
| Type | Text-to-image model |
| Website | deepmind |
The original version of the model was first discussed in a paper from May 2022.[2] The tool produces high-quality images and is available to all users with a Google account through services including Gemini, ImageFX, and Vertex AI.[3]
History
Imagen's original version was first presented in a paper published in May 2022. It featured the ability to generate high-fidelity images from natural language.[2] The second version, Imagen 2 was released in December 2023.[4] The standout feature was text and logo generation.[5] Imagen 3 was released in August 2024.[6] Google claims that the newest version provides better detail and lighting on generated images.[7]
Technology
Imagen uses two key technologies. The first is the use of transformer-based large language models, notably T5, to understand text and subsequently encode text for image synthesis. The second is the use of cascaded diffusion models providing high-fidelity image generation. It generates image in three stages, starting from a base of 64x64, then upsampled to 256x256 and 1024x1024.[2]
Capabilities
Imagen can generate photorealistic images from text prompts.[3] It can also create various styles, such as cinematic, 35mm film, illustration, and surreal. The model can generate images in five aspect ratios, namely 9:16, 3:4, 1:1, 4:3, and 16:9. Imagen can also refine already generated images by editing existing text prompts.[7]
See also
References
External links
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