# Pastiche Master: Exemplar-Based High-Resolution Portrait Style Transfer

arXiv: https://arxiv.org/abs/2203.13248 · HTML: https://mlsanity.com/paper/2203.13248/

## Key facts

- Cited by 66 papers in the map (data through 14 Oct 2026).
- Builds on 31 of its 42 references that are in the map.
- First posted on arXiv 24 Mar 2022.

## Builds on (most cited first, 30 of 31)

- [Deep Residual Learning for Image Recognition](https://mlsanity.com/paper/1512.03385/) (2015)
- [Very Deep Convolutional Networks for Large-Scale Image Recognition](https://mlsanity.com/paper/1409.1556/) (2014)
- [A Style-Based Generator Architecture for Generative Adversarial Networks](https://mlsanity.com/paper/1812.04948/) (2018)
- [Deep Learning Face Attributes in the Wild](https://mlsanity.com/paper/1411.7766/) (2014)
- [Analyzing and Improving the Image Quality of StyleGAN](https://mlsanity.com/paper/1912.04958/) (2019)
- [Progressive Growing of GANs for Improved Quality, Stability, and Variation](https://mlsanity.com/paper/1710.10196/) (2017)
- [Perceptual Losses for Real-Time Style Transfer and Super-Resolution](https://mlsanity.com/paper/1603.08155/) (2016)
- [Arbitrary Style Transfer in Real-time with Adaptive Instance Normalization](https://mlsanity.com/paper/1703.06868/) (2017)
- [StarGAN v2: Diverse Image Synthesis for Multiple Domains](https://mlsanity.com/paper/1912.01865/) (2019)
- [Encoding in Style: a StyleGAN Encoder for Image-to-Image Translation](https://mlsanity.com/paper/2008.00951/) (2020)
- [Image2StyleGAN: How to Embed Images Into the StyleGAN Latent Space?](https://mlsanity.com/paper/1904.03189/) (2019)
- [Few-shot Image Generation via Cross-domain Correspondence](https://mlsanity.com/paper/2104.06820/) (2021)
- [U-GAT-IT: Unsupervised Generative Attentional Networks with Adaptive Layer-Instance Normalization for Image-to-Image Translation](https://mlsanity.com/paper/1907.10830/) (2019)
- [The Contextual Loss for Image Transformation with Non-Aligned Data](https://mlsanity.com/paper/1803.02077/) (2018)
- [Visual Attribute Transfer through Deep Image Analogy](https://mlsanity.com/paper/1705.01088/) (2017)
- [Combining Markov Random Fields and Convolutional Neural Networks for Image Synthesis](https://mlsanity.com/paper/1601.04589/) (2016)
- [Resolution Dependent GAN Interpolation for Controllable Image Synthesis Between Domains](https://mlsanity.com/paper/2010.05334/) (2020)
- [Deceive D: Adaptive Pseudo Augmentation for GAN Training with Limited Data](https://mlsanity.com/paper/2111.06849/) (2021)
- [StyleAlign: Analysis and Applications of Aligned StyleGAN Models](https://mlsanity.com/paper/2110.11323/) (2021)
- [Unpaired Image-to-Image Translation using Adversarial Consistency Loss](https://mlsanity.com/paper/2003.04858/) (2020)
- [Breaking the cycle -- Colleagues are all you need](https://mlsanity.com/paper/1911.10538/) (2019)
- [Unsupervised Image-to-Image Translation via Pre-trained StyleGAN2 Network](https://mlsanity.com/paper/2010.05713/) (2020)
- [Diagonal Attention and Style-based GAN for Content-Style Disentanglement in Image Generation and Translation](https://mlsanity.com/paper/2103.16146/) (2021)
- [WarpGAN: Automatic Caricature Generation](https://mlsanity.com/paper/1811.10100/) (2018)
- [AniGAN: Style-Guided Generative Adversarial Networks for Unsupervised Anime Face Generation](https://mlsanity.com/paper/2102.12593/) (2021)
- [Non-Adversarial Image Synthesis with Generative Latent Nearest Neighbors](https://mlsanity.com/paper/1812.08985/) (2018)
- [SPatchGAN: A Statistical Feature Based Discriminator for Unsupervised Image-to-Image Translation](https://mlsanity.com/paper/2103.16219/) (2021)
- [GANs N' Roses: Stable, Controllable, Diverse Image to Image Translation (works for videos too!)](https://mlsanity.com/paper/2106.06561/) (2021)
- [Unaligned Image-to-Image Translation by Learning to Reweight](https://mlsanity.com/paper/2109.11736/) (2021)
- [CariGANs: Unpaired Photo-to-Caricature Translation](https://mlsanity.com/paper/1811.00222/) (2018)

## Built on by (most cited first, 30 of 66)

- [Drag Your Noise: Interactive Point-based Editing via Diffusion Semantic Propagation](https://mlsanity.com/paper/2404.01050/) (2024)
- [ArtFID: Quantitative Evaluation of Neural Style Transfer](https://mlsanity.com/paper/2207.12280/) (2022)
- [3DAvatarGAN: Bridging Domains for Personalized Editable Avatars](https://mlsanity.com/paper/2301.02700/) (2023)
- [EmoGen: Emotional Image Content Generation with Text-to-Image Diffusion Models](https://mlsanity.com/paper/2401.04608/) (2024)
- [Holo-Relighting: Controllable Volumetric Portrait Relighting from a Single Image](https://mlsanity.com/paper/2403.09632/) (2024)
- [Text2Human: Text-Driven Controllable Human Image Generation](https://mlsanity.com/paper/2205.15996/) (2022)
- [A Survey of Representation Learning, Optimization Strategies, and Applications for Omnidirectional Vision](https://mlsanity.com/paper/2502.10444/) (2025)
- [VToonify: Controllable High-Resolution Portrait Video Style Transfer](https://mlsanity.com/paper/2209.11224/) (2022)
- [Scenimefy: Learning to Craft Anime Scene via Semi-Supervised Image-to-Image Translation](https://mlsanity.com/paper/2308.12968/) (2023)
- [Deformable One-shot Face Stylization via DINO Semantic Guidance](https://mlsanity.com/paper/2403.00459/) (2024)
- [WeditGAN: Few-Shot Image Generation via Latent Space Relocation](https://mlsanity.com/paper/2305.06671/) (2023)
- [Expanding Expressiveness of Diffusion Models with Limited Data via Self-Distillation based Fine-Tuning](https://mlsanity.com/paper/2311.01018/) (2023)
- [Portrait Diffusion: Training-free Face Stylization with Chain-of-Painting](https://mlsanity.com/paper/2312.02212/) (2023)
- [Real-time 3D-aware Portrait Editing from a Single Image](https://mlsanity.com/paper/2402.14000/) (2024)
- [Image Synthesis under Limited Data: A Survey and Taxonomy](https://mlsanity.com/paper/2307.16879/) (2023)
- [DeformToon3D: Deformable 3D Toonification from Neural Radiance Fields](https://mlsanity.com/paper/2309.04410/) (2023)
- [Dr.3D: Adapting 3D GANs to Artistic Drawings](https://mlsanity.com/paper/2211.16798/) (2022)
- [Advances in 3D Neural Stylization: A Survey](https://mlsanity.com/paper/2311.18328/) (2023)
- [FlipSketch: Flipping Static Drawings to Text-Guided Sketch Animations](https://mlsanity.com/paper/2411.10818/) (2024)
- [What Decreases Editing Capability? Domain-Specific Hybrid Refinement for Improved GAN Inversion](https://mlsanity.com/paper/2301.12141/) (2023)
- [AniFaceDrawing: Anime Portrait Exploration during Your Sketching](https://mlsanity.com/paper/2306.07476/) (2023)
- [GaussianStyle: Gaussian Head Avatar via StyleGAN](https://mlsanity.com/paper/2402.00827/) (2024)
- [Generalizable Face Landmarking Guided by Conditional Face Warping](https://mlsanity.com/paper/2404.12322/) (2024)
- [DiffFaceSketch: High-Fidelity Face Image Synthesis with Sketch-Guided Latent Diffusion Model](https://mlsanity.com/paper/2302.06908/) (2023)
- [AgileGAN3D: Few-Shot 3D Portrait Stylization by Augmented Transfer Learning](https://mlsanity.com/paper/2303.14297/) (2023)
- [LSAP: Rethinking Inversion Fidelity, Perception and Editability in GAN Latent Space](https://mlsanity.com/paper/2209.12746/) (2022)
- [Fix the Noise: Disentangling Source Feature for Controllable Domain Translation](https://mlsanity.com/paper/2303.11545/) (2023)
- [AlteredAvatar: Stylizing Dynamic 3D Avatars with Fast Style Adaptation](https://mlsanity.com/paper/2305.19245/) (2023)
- [Stylized Face Sketch Extraction via Generative Prior with Limited Data](https://mlsanity.com/paper/2403.11263/) (2024)
- [LeGO: Leveraging a Surface Deformation Network for Animatable Stylized Face Generation with One Example](https://mlsanity.com/paper/2403.15227/) (2024)

## Abstract (arXiv)

Recent studies on StyleGAN show high performance on artistic portrait generation by transfer learning with limited data. In this paper, we explore more challenging exemplar-based high-resolution portrait style transfer by introducing a novel DualStyleGAN with flexible control of dual styles of the original face domain and the extended artistic portrait domain. Different from StyleGAN, DualStyleGAN provides a natural way of style transfer by characterizing the content and style of a portrait with an intrinsic style path and a new extrinsic style path, respectively. The delicately designed extrinsic style path enables our model to modulate both the color and complex structural styles hierarchically to precisely pastiche the style example. Furthermore, a novel progressive fine-tuning scheme is introduced to smoothly transform the generative space of the model to the target domain, even with the above modifications on the network architecture. Experiments demonstrate the superiority of DualStyleGAN over state-of-the-art methods in high-quality portrait style transfer and flexible style control.