HolmesShuan/Zero-shot-Style-Transfer-via-Attention-Rearrangement
[CVPR2024] Official implementation of the paper "Z∗: Zero-shot Style Transfer via Attention Rearrangement" a.k.a. "Z∗: Zero-shot Style Transfer via Attention Reweighting"
This project helps graphic designers and artists transform the visual style of an image without needing to train a special model first. You provide a content image (what you want to stylize) and a style image (the look you want to apply), and it generates a new image with the content of the first and the style of the second. It's ideal for anyone creating visual content who wants to quickly experiment with different artistic styles.
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Use this if you need to apply a new artistic style to an image instantly, without any setup or training for each new style.
Not ideal if you need fine-grained control over specific stylistic elements beyond what a general diffusion model can provide, or if you don't have access to the necessary computational resources for running image generation models.
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Language
Python
License
Apache-2.0
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Last pushed
Sep 29, 2024
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