What is DreamBooth AI?

DreamBooth is a subject-driven generation model that fine-tunes existing text-to-image diffusion models.

The AI tool was developed by a group of researchers from Google and Boston University.

How does it work?

You feed it with 3–5 photos of your subject. Then, the AI synthesizes the subject into a different context to produce a brand new image whilst maintaining the features.

Here’s an example.

Transform to different art styles

DreamBooth will not just take your photo to different places; it can make artistic renditions in the style of famous painters and sculptors as well.

Isn’t that cool?

You no longer have to pay professional artists and wait for days to get finished. AI can generate a bunch of artistic renditions fast and high-quality.

How about adding accessories to your dog?

No problem. The AI’s “Accessorization” capability can add whatever accessories or outfits you wish.

This must be an exciting feature for all pet owners out there.

Other notable capabilities

• Text-Guided View Synthesis — the AI can render the subject from different angles and poses.
• Property Modification — the AI can do color modifications and even make hybrids with different animals.

It works with other image generators

Several developers have already tested DreamBooth with Stable Diffusion.

If you're interested in exploring the capabilities of DreamBooth AI, you may also want to check out our guides on "How to generate AI Avatars with Stable Diffusion API?" and "How to Finetune Dreambooth Model". The Stable Diffusion API provides a powerful platform for generating custom avatars, while Dreambooth AI offers a range of pre-built models that can be further fine-tuned to meet your specific needs. By combining the strengths of both tools, you can quickly and easily create high-quality avatars that perfectly reflect your vision. So, if you're interested in exploring the full potential of DreamBooth AI and Stable Diffusion API, be sure to check out our guides on generating AI avatars and finetuning Dreambooth models.

Check out this GitHub repo from user Xavier Xiao; the usage instructions are all in there if you want to try it.