UniBester/AGE
A implementation of Attribute Group Editing for Reliable Few-shot Image Generation (CVPR 2022)
This project helps visual content creators and researchers generate diverse, realistic images for categories with very limited examples. You provide a few images of a new object or animal, and the system can create many more variations, even without extensive retraining. It's designed for anyone needing to expand visual datasets for underrepresented subjects.
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Use this if you need to generate high-quality, varied images for subjects where you only have a handful of existing pictures, like rare animal species, specific product variants, or unique facial expressions.
Not ideal if you already have large datasets for your image categories or if you need to generate images from scratch without any existing examples.
Stars
59
Forks
7
Language
Python
License
MIT
Category
Last pushed
Apr 12, 2022
Commits (30d)
0
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