# Vectorized Region Based Brush Strokes for Artistic Rendering

arXiv: https://arxiv.org/abs/2506.09969 · HTML: https://mlsanity.com/paper/2506.09969/

## Key facts

- Cited by 2 papers in the map (data through 14 Oct 2026).
- Builds on 18 of its 40 references that are in the map.
- First posted on arXiv 11 Jun 2025.

## Builds on (most cited first, 18 of 18)

- [Segment Anything](https://mlsanity.com/paper/2304.02643/) (2023)
- [End-to-End Object Detection with Transformers](https://mlsanity.com/paper/2005.12872/) (2020)
- [A Style-Based Generator Architecture for Generative Adversarial Networks](https://mlsanity.com/paper/1812.04948/) (2018)
- [Depth Anything: Unleashing the Power of Large-Scale Unlabeled Data](https://mlsanity.com/paper/2401.10891/) (2024)
- [Training Generative Adversarial Networks with Limited Data](https://mlsanity.com/paper/2006.06676/) (2020)
- [Large-scale Classification of Fine-Art Paintings: Learning The Right Metric on The Right Feature](https://mlsanity.com/paper/1505.00855/) (2015)
- [Learning to Paint With Model-based Deep Reinforcement Learning](https://mlsanity.com/paper/1903.04411/) (2019)
- [Pastiche Master: Exemplar-Based High-Resolution Portrait Style Transfer](https://mlsanity.com/paper/2203.13248/) (2022)
- [Paint Transformer: Feed Forward Neural Painting with Stroke Prediction](https://mlsanity.com/paper/2108.03798/) (2021)
- [Stylized Neural Painting](https://mlsanity.com/paper/2011.08114/) (2020)
- [ProcessPainter: Learn Painting Process from Sequence Data](https://mlsanity.com/paper/2406.06062/) (2024)
- [Stroke-based Neural Painting and Stylization with Dynamically Predicted Painting Region](https://mlsanity.com/paper/2309.03504/) (2023)
- [Im2Oil: Stroke-Based Oil Painting Rendering with Linearly Controllable Fineness Via Adaptive Sampling](https://mlsanity.com/paper/2209.13219/) (2022)
- [DELAUNAY: a dataset of abstract art for psychophysical and machine learning research](https://mlsanity.com/paper/2201.12123/) (2022)
- [Stroke-based Rendering: From Heuristics to Deep Learning](https://mlsanity.com/paper/2302.00595/) (2022)
- [Segmentation-Based Parametric Painting](https://mlsanity.com/paper/2311.14271/) (2023)
- [Polygon Area Decomposition Using a Compactness Metric](https://mlsanity.com/paper/2110.04043/) (2021)
- [Sketch & Paint: Stroke-by-Stroke Evolution of Visual Artworks](https://mlsanity.com/paper/2502.20119/) (2025)

## Built on by (most cited first, 2 of 2)

- [Differentiable Stroke Planning with Dual Parameterization for Efficient and High-Fidelity Painting Creation](https://mlsanity.com/paper/2604.02752/) (2026)
- [PaintCopilot: Modeling Painting as Autonomous Artistic Continuation](https://mlsanity.com/paper/2605.20941/) (2026)

## Abstract (arXiv)

Creating a stroke-by-stroke evolution process of a visual artwork tries to bridge the emotional and educational gap between the finished static artwork and its creation process. Recent stroke-based painting systems focus on capturing stroke details by predicting and iteratively refining stroke parameters to maximize the similarity between the input image and the rendered output. However, these methods often struggle to produce stroke compositions that align with artistic principles and intent. To address this, we explore an image-to-painting method that (i) facilitates semantic guidance for brush strokes in targeted regions, (ii) computes the brush stroke parameters, and (iii) establishes a sequence among segments and strokes to sequentially render the final painting. Experimental results on various input image types, such as face images, paintings, and photographic images, show that our method aligns with a region-based painting strategy while rendering a painting with high fidelity and superior stroke quality.