# Example-Guided Style Consistent Image Synthesis from Semantic Labeling

arXiv: https://arxiv.org/abs/1906.01314 · HTML: https://mlsanity.com/paper/1906.01314/

## Key facts

- Cited by 29 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 4 Jun 2019.

## Built on by (most cited first, 29 of 29)

- [Enhancing Photorealism Enhancement](https://mlsanity.com/paper/2105.04619/) (2021)
- [ImageBrush: Learning Visual In-Context Instructions for Exemplar-Based Image Manipulation](https://mlsanity.com/paper/2308.00906/) (2023)
- [Photoswap: Personalized Subject Swapping in Images](https://mlsanity.com/paper/2305.18286/) (2023)
- [Unbalanced Feature Transport for Exemplar-based Image Translation](https://mlsanity.com/paper/2106.10482/) (2021)
- [User-Controllable Latent Transformer for StyleGAN Image Layout Editing](https://mlsanity.com/paper/2208.12408/) (2022)
- [Discover, Hallucinate, and Adapt: Open Compound Domain Adaptation for Semantic Segmentation](https://mlsanity.com/paper/2110.04111/) (2021)
- [DynaST: Dynamic Sparse Transformer for Exemplar-Guided Image Generation](https://mlsanity.com/paper/2207.06124/) (2022)
- [MIDMs: Matching Interleaved Diffusion Models for Exemplar-based Image Translation](https://mlsanity.com/paper/2209.11047/) (2022)
- [Semi-supervised Synthesis of High-Resolution Editable Textures for 3D Humans](https://mlsanity.com/paper/2103.17266/) (2021)
- [Bi-level Feature Alignment for Versatile Image Translation and Manipulation](https://mlsanity.com/paper/2107.03021/) (2021)
- [SwapAnything: Enabling Arbitrary Object Swapping in Personalized Visual Editing](https://mlsanity.com/paper/2404.05717/) (2024)
- [Total Generate: Cycle in Cycle Generative Adversarial Networks for Generating Human Faces, Hands, Bodies, and Natural Scenes](https://mlsanity.com/paper/2106.10876/) (2021)
- [Auto-regressive Image Synthesis with Integrated Quantization](https://mlsanity.com/paper/2207.10776/) (2022)
- [Deep Image Synthesis from Intuitive User Input: A Review and Perspectives](https://mlsanity.com/paper/2107.04240/) (2021)
- [FoundHand: Large-Scale Domain-Specific Learning for Controllable Hand Image Generation](https://mlsanity.com/paper/2412.02690/) (2024)
- [Harnessing the Conditioning Sensorium for Improved Image Translation](https://mlsanity.com/paper/2110.06443/) (2021)
- [Generative Adversarial Networks for Image Augmentation in Agriculture: A Systematic Review](https://mlsanity.com/paper/2204.04707/) (2022)
- [Multiple GAN Inversion for Exemplar-based Image-to-Image Translation](https://mlsanity.com/paper/2103.14471/) (2021)
- [Reasoning Structural Relation for Occlusion-Robust Facial Landmark Localization](https://mlsanity.com/paper/2112.10087/) (2021)
- [ScoreMix: A Scalable Augmentation Strategy for Training GANs with Limited Data](https://mlsanity.com/paper/2210.15137/) (2022)
- [CFFT-GAN: Cross-domain Feature Fusion Transformer for Exemplar-based Image Translation](https://mlsanity.com/paper/2302.01608/) (2023)
- [Controllable Multi-domain Semantic Artwork Synthesis](https://mlsanity.com/paper/2308.10111/) (2023)
- [Semantic Approach to Quantifying the Consistency of Diffusion Model Image Generation](https://mlsanity.com/paper/2404.08799/) (2024)
- [Tuning-Free Visual Customization via View Iterative Self-Attention Control](https://mlsanity.com/paper/2406.06258/) (2024)
- [Adapted Human Pose: Monocular 3D Human Pose Estimation with Zero Real 3D Pose Data](https://mlsanity.com/paper/2105.10837/) (2021)
- [Semantic-aware Network for Aerial-to-Ground Image Synthesis](https://mlsanity.com/paper/2308.06945/) (2023)
- [SpecDM: Hyperspectral Dataset Synthesis with Pixel-level Semantic Annotations](https://mlsanity.com/paper/2502.17056/) (2025)
- [Image-to-image Transformation with Auxiliary Condition](https://mlsanity.com/paper/2106.13696/) (2021)
- [Semantic Map Injected GAN Training for Image-to-Image Translation](https://mlsanity.com/paper/2112.01845/) (2021)

## Abstract (arXiv)

Example-guided image synthesis aims to synthesize an image from a semantic label map and an exemplary image indicating style. We use the term "style" in this problem to refer to implicit characteristics of images, for example: in portraits "style" includes gender, racial identity, age, hairstyle; in full body pictures it includes clothing; in street scenes, it refers to weather and time of day and such like. A semantic label map in these cases indicates facial expression, full body pose, or scene segmentation. We propose a solution to the example-guided image synthesis problem using conditional generative adversarial networks with style consistency. Our key contributions are (i) a novel style consistency discriminator to determine whether a pair of images are consistent in style; (ii) an adaptive semantic consistency loss; and (iii) a training data sampling strategy, for synthesizing style-consistent results to the exemplar.