Ha0Tang/AttentionGAN
AttentionGAN for Unpaired Image-to-Image Translation & Multi-Domain Image-to-Image Translation
This project helps graphic designers, content creators, or researchers to automatically transform images from one visual style or domain to another without needing paired examples. You input a collection of images from a source domain (e.g., photos of horses) and a collection from a target domain (e.g., photos of zebras), and it generates new images where the subjects from the source adopt the characteristics of the target. This is ideal for those who need to generate diverse image variations or conduct visual concept exploration.
688 stars. No commits in the last 6 months.
Use this if you need to convert images between distinct visual categories, like turning a selfie into an anime character or a map into an aerial photo, where direct one-to-one examples aren't available for training.
Not ideal if you need pixel-perfect, highly accurate transformations that maintain exact object structures or if your target domain requires precise geometric changes not represented in the source.
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688
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102
Language
Python
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Last pushed
Jul 06, 2023
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