BenjaminJonghyun/SuperStyleNet
SuperStyleNet: Deep Image Synthesis with Superpixel Based Style Encoder (BMVC 2021)
This project helps create highly detailed, realistic images by transferring specific visual styles from one image to another, focusing on preserving small-scale object details. You provide a content image and one or more style images, along with their semantic masks (e.g., outlining hair, skin, or buildings). The output is a new image where the content's structure is retained, but its appearance adopts the nuanced styles from the sources. This tool is for researchers and practitioners in computer vision and digital art who need precise style transfer.
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Use this if you need to generate high-quality images with precise control over style transfer, especially when preserving fine details and local stylistic elements across different parts of an image is crucial.
Not ideal if you are looking for a simple, out-of-the-box style transfer application without needing to prepare semantic masks or manage deep learning model training.
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27
Forks
3
Language
Python
License
MIT
Category
Last pushed
Dec 28, 2021
Commits (30d)
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