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Everything about StyleGAN
Novel generative adversarial network
The Style Generative Adversarial Network, or StyleGAN for short, is an extension to the GAN architecture introduced by Nvidia researchers in December 2018, and made source available in February 2019. Wikipedia →
🧭 Start here: a 6-step reading path
- Read the overview: StyleGANA 5-minute orientation
- Skim a recent paper: E2Style: Improve the Efficiency and Effectiveness of StyleGAN InversionInfluential work since 2022
- Pick up a classic book: Database Management Using AIThe most-reprinted book on the subject
- Read the landmark paper: Designing an encoder for StyleGAN image manipulationCited 742 times
- Go sideways: Generative adversarial networkA closely related topic
- Go sideways: Fréchet inception distanceA closely related topic
📖 Definitions
No dictionary entry for this exact phrase.
🗂️ The subject at a glance
🏆 Landmark papers (most cited)
Designing an encoder for StyleGAN image manipulation
StyleGAN-NADA
StyleFlow: Attribute-conditioned Exploration of StyleGAN-Generated Images using Conditional Continuous Normalizing Flows
Dermoscopy Image Classification Based on StyleGAN and DenseNet201
Face Generation and Editing With StyleGAN: A Survey
State‐of‐the‐Art in the Architecture, Methods and Applications of StyleGAN
SDF‐StyleGAN: Implicit SDF‐Based StyleGAN for 3D Shape Generation
Latent space manipulation for high-resolution medical image synthesis via the StyleGAN
🆕 Influential since 2022
E2Style: Improve the Efficiency and Effectiveness of StyleGAN Inversion
Self-supervised representation learning anomaly detection methodology based on boosting algorithms enhanced by data augmentation using StyleGAN for manufacturing imbalanced data
User‐Controllable Latent Transformer for StyleGAN Image Layout Editing
MOST-GAN: 3D Morphable StyleGAN for Disentangled Face Image Manipulation
Scalable Face Image Coding via StyleGAN Prior: Toward Compression for Human-Machine Collaborative Vision
📚 Books worth reading
Database Management Using AI · 2024
Ranked by number of editions on Open Library, a rough measure of how lasting a book is.
🔗 Related topics
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- Fréchet inception distance The Fréchet inception distance (FID) is a metric used to assess the quality of images created by a generative model, like a generative adversarial network…
- Energy-based model An energy-based model (EBM), also called Canonical Ensemble Learning (CEL) or Learning via Canonical Ensemble (LCE), is an application of canonical ensemble…
- Wasserstein GAN The Wasserstein Generative Adversarial Network (WGAN) is a variant of generative adversarial network (GAN) proposed in 2017 that aims to "improve the stability…
- Inception score The Inception Score (IS) is an algorithm used to assess the quality of images created by a generative image model such as a generative adversarial network…
- String diagram In mathematics, string diagrams are a formal graphical language for representing morphisms in monoidal categories, or more generally 2-cells in 2-categories…
- Variational autoencoder In machine learning, a variational autoencoder (VAE) is an artificial neural network architecture introduced by Diederik P. Kingma and Max Welling in 2013…
- Generator (category theory) In mathematics, more specifically category theory, a generator (otherwise known as a separator), or generating family (resp. separating family) is a collection…