# Free-hand Sketch Synthesis with Deformable Stroke Models

arXiv: https://arxiv.org/abs/1510.02644 · HTML: https://mlsanity.com/paper/1510.02644/

## Key facts

- Cited by 16 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 9 Oct 2015.

## Built on by (most cited first, 16 of 16)

- [CLIPascene: Scene Sketching with Different Types and Levels of Abstraction](https://mlsanity.com/paper/2211.17256/) (2022)
- [CLIPasso: Semantically-Aware Object Sketching](https://mlsanity.com/paper/2202.05822/) (2022)
- [DiffSketcher: Text Guided Vector Sketch Synthesis through Latent Diffusion Models](https://mlsanity.com/paper/2306.14685/) (2023)
- [Breathing Life Into Sketches Using Text-to-Video Priors](https://mlsanity.com/paper/2311.13608/) (2023)
- [SketchAgent: Language-Driven Sequential Sketch Generation](https://mlsanity.com/paper/2411.17673/) (2024)
- [DoodleFormer: Creative Sketch Drawing with Transformers](https://mlsanity.com/paper/2112.03258/) (2021)
- [Facial-Sketch Synthesis: A New Challenge](https://mlsanity.com/paper/2112.15439/) (2021)
- [Multi-Object Sketch Animation with Grouping and Motion Trajectory Priors](https://mlsanity.com/paper/2508.15535/) (2025)
- [Semi-supervised reference-based sketch extraction using a contrastive learning framework](https://mlsanity.com/paper/2407.14026/) (2024)
- [Query-guided Attention in Vision Transformers for Localizing Objects Using a Single Sketch](https://mlsanity.com/paper/2303.08784/) (2023)
- [DifferSketching: How Differently Do People Sketch 3D Objects?](https://mlsanity.com/paper/2209.08791/) (2022)
- [A Creative Industry Image Generation Dataset Based on Captions](https://mlsanity.com/paper/2211.09035/) (2022)
- [ShadowDraw: From Any Object to Shadow-Drawing Compositional Art](https://mlsanity.com/paper/2512.05110/) (2025)
- [SketchBodyNet: A Sketch-Driven Multi-faceted Decoder Network for 3D Human Reconstruction](https://mlsanity.com/paper/2310.06577/) (2023)
- [CLIPDraw++: Text-to-Sketch Synthesis with Simple Primitives](https://mlsanity.com/paper/2312.02345/) (2023)
- [Generative Visual Communication in the Era of Vision-Language Models](https://mlsanity.com/paper/2411.18727/) (2024)

## Abstract (arXiv)

We present a generative model which can automatically summarize the stroke composition of free-hand sketches of a given category. When our model is fit to a collection of sketches with similar poses, it discovers and learns the structure and appearance of a set of coherent parts, with each part represented by a group of strokes. It represents both consistent (topology) as well as diverse aspects (structure and appearance variations) of each sketch category. Key to the success of our model are important insights learned from a comprehensive study performed on human stroke data. By fitting this model to images, we are able to synthesize visually similar and pleasant free-hand sketches.