# Deep Painterly Harmonization

arXiv: https://arxiv.org/abs/1804.03189 · HTML: https://mlsanity.com/paper/1804.03189/

## Key facts

- Cited by 19 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 9 Apr 2018.

## Built on by (most cited first, 19 of 19)

- [ARF: Artistic Radiance Fields](https://mlsanity.com/paper/2206.06360/) (2022)
- [Making Images Real Again: A Comprehensive Survey on Deep Image Composition](https://mlsanity.com/paper/2106.14490/) (2021)
- [Harmonizer: Learning to Perform White-Box Image and Video Harmonization](https://mlsanity.com/paper/2207.01322/) (2022)
- [Image-Based CLIP-Guided Essence Transfer](https://mlsanity.com/paper/2110.12427/) (2021)
- [SCS-Co: Self-Consistent Style Contrastive Learning for Image Harmonization](https://mlsanity.com/paper/2204.13962/) (2022)
- [Geometry Transfer for Stylizing Radiance Fields](https://mlsanity.com/paper/2402.00863/) (2024)
- [SinIR: Efficient General Image Manipulation with Single Image Reconstruction](https://mlsanity.com/paper/2106.07140/) (2021)
- [Painterly Image Harmonization using Diffusion Model](https://mlsanity.com/paper/2308.02228/) (2023)
- [Painterly Image Harmonization in Dual Domains](https://mlsanity.com/paper/2212.08846/) (2022)
- [Location-Free Camouflage Generation Network](https://mlsanity.com/paper/2203.09845/) (2022)
- [FreePIH: Training-Free Painterly Image Harmonization with Diffusion Model](https://mlsanity.com/paper/2311.14926/) (2023)
- [Reference-based Painterly Inpainting via Diffusion: Crossing the Wild Reference Domain Gap](https://mlsanity.com/paper/2307.10584/) (2023)
- [Painterly Image Harmonization by Learning from Painterly Objects](https://mlsanity.com/paper/2312.10263/) (2023)
- [Line Drawing Guided Progressive Inpainting of Mural Damage](https://mlsanity.com/paper/2211.06649/) (2022)
- [Progressive Painterly Image Harmonization from Low-level Styles to High-level Styles](https://mlsanity.com/paper/2312.10264/) (2023)
- [Neural Policy Style Transfer](https://mlsanity.com/paper/2402.00677/) (2024)
- [Intensity Harmonization for Airborne LiDAR](https://mlsanity.com/paper/2105.01793/) (2021)
- [Unsupervised COVID-19 Lesion Segmentation in CT Using Cycle Consistent Generative Adversarial Network](https://mlsanity.com/paper/2111.11602/) (2021)
- [Painterly Image Harmonization via Adversarial Residual Learning](https://mlsanity.com/paper/2311.08646/) (2023)

## Abstract (arXiv)

Copying an element from a photo and pasting it into a painting is a challenging task. Applying photo compositing techniques in this context yields subpar results that look like a collage --- and existing painterly stylization algorithms, which are global, perform poorly when applied locally. We address these issues with a dedicated algorithm that carefully determines the local statistics to be transferred. We ensure both spatial and inter-scale statistical consistency and demonstrate that both aspects are key to generating quality results. To cope with the diversity of abstraction levels and types of paintings, we introduce a technique to adjust the parameters of the transfer depending on the painting. We show that our algorithm produces significantly better results than photo compositing or global stylization techniques and that it enables creative painterly edits that would be otherwise difficult to achieve.