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StyleSketch

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Stylized Face Sketch Extraction via Generative Prior with Limited Data

4.7
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Inputs: image
Type
Saas
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About StyleSketch

StyleSketch is a method for extracting high-resolution stylized face sketches from a single face image, leveraging the deep features of a pretrained StyleGAN. It can be trained with as few as 16 pairs of face and corresponding sketch images, using part-based losses and a two-stage learning strategy for fast convergence. The approach outperforms existing state-of-the-art sketch extraction and few-shot image adaptation methods, and can be extended to other domains (e.g., animals, objects) while also enabling semantic editing of the resulting sketches.

Key Features

Trained with as few as 16 paired face-sketch images
Uses deep features from pretrained StyleGAN as input
Part-based losses with two-stage learning for fast convergence
Produces high-resolution abstract sketches
Supports semantic editing of extracted sketches
Extensible to non-face domains (e.g., animals, objects)

Pros & Cons

Pros
  • Requires only 16 paired images for training, significantly less than competing methods
  • Outperforms existing state-of-the-art sketch extraction and few-shot adaptation methods
  • Generates high-resolution (1024×1024) abstract sketches
  • Enables semantic editing of the extracted sketch via StyleGAN's feature space
  • Applicable to multiple domains without retraining the full model
Cons
  • Relies on a pretrained StyleGAN, which may not be available for all domains
  • Sketch extraction requires GAN inversion of the input image, adding computational overhead
  • Training requires paired sketch data (face + sketch), which may be difficult to obtain for arbitrary styles
  • Primarily designed for face sketches; extension to other domains may require additional tuning

Best For

Stylized face sketch extraction from a single photoArtistic face representation with limited training dataSemantic editing of face sketches (e.g., modifying facial attributes)Sketch extraction in domains beyond faces (e.g., animals, objects)

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FAQ

What is StyleSketch?
StyleSketch is a research method for extracting high-resolution stylized face sketches from a single face image, using a pretrained StyleGAN as generative prior. It can be trained with as few as 16 paired face-sketch images.
How many training images does StyleSketch require?
StyleSketch requires only 16 pairs of face images and their corresponding sketch images for training.
What are the key technical components of StyleSketch?
StyleSketch uses deep features from a pretrained StyleGAN, part-based losses, and a two-stage learning strategy to achieve fast convergence and high-quality sketch extraction.
Can StyleSketch be used for non-face images?
Yes, the authors demonstrate extending StyleSketch to other domains such as animals and objects for sketch extraction.
Does StyleSketch support editing the extracted sketch?
Yes, StyleSketch enables semantic editing of the extracted face sketches by manipulating the latent space of the StyleGAN.