

Stylesketch
Overview :
StyleSketch is a method for extracting high-resolution stylized sketches from facial images. Leveraging the rich semantic information of deep features from the pre-trained StyleGAN, it can train a sketch generator using only 16 pairs of face and corresponding sketch images. Through stage-wise learning and partial losses, StyleSketch achieves rapid convergence and extracts high-quality sketches. Compared to existing state-of-the-art sketch extraction methods and few-shot sample adaptation methods, StyleSketch demonstrates superior performance in extracting high-resolution abstract facial sketches.
Target Users :
Suitable for researchers in the fields of computer vision and image processing, as well as developers interested in artistic creation and stylized image generation.
Use Cases
Researchers use StyleSketch to extract sketches from celebrity photos for an art exhibition
Developers leverage StyleSketch to create personalized avatar sketch filters for social media applications
Artists utilize StyleSketch to explore different sketch styles and create unique artworks
Features
Extracts stylized sketches from facial images
Utilizes deep features from pre-trained StyleGAN for training
Achieves rapid convergence through partial losses and two-stage learning
Showcases StyleSketch's applications in other domains and possibilities for semantic editing
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