SHI-Labs/StyleNAT
New flexible and efficient image generation framework that sets new SOTA on FFHQ-256 with FID 2.05, 2022
This is a framework for generating high-quality, realistic images, specifically of human faces and churches, with superior efficiency. You input training datasets of images, and it outputs a model capable of generating new, unique images that match the style and characteristics of the training data. This tool is for researchers and practitioners in computer vision or digital content creation who need to synthesize high-fidelity visual content.
102 stars. No commits in the last 6 months.
Use this if you need to generate high-resolution, photorealistic images from scratch, particularly for datasets like human faces or architectural structures, with a focus on efficiency and quality.
Not ideal if you're looking for a simple, out-of-the-box image editor or a tool for generating images based on text prompts rather than learned styles.
Stars
102
Forks
13
Language
Python
License
MIT
Category
Last pushed
Jun 26, 2025
Commits (30d)
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