DomainGallery: Few-shot Domain-driven Image Generation by Attribute-centric Finetuning

Understand

The recent progress in text-to-image models pretrained on large-scale datasets has enabled us to generate various images as long as we provide a text prompt describing what we want.

• Nevertheless, the availability of these models is still limited when we expect to generate images that fall into a specific domain either hard to describe or just unseen to the models.
• In this work, we propose DomainGallery, a few-shot domain-driven image generation method which aims at finetuning pretrained Stable Diffusion on few-shot target datasets in an attribute-centric manner.
• Specifically, DomainGallery features prior attribute erasure, attribute disentanglement, regularization and enhancement.