Single-Line Drawing Generation via Semantics-Driven Optimization
Computer Graphics Forum (CGF), presented at Symposium on Geometry Processing2026
Abstract
Line drawings are a highly expressive art form that requires the artist to abstract and distill the essence of their subject. We present the first semantics-driven method for automatically generating single-line drawings in vector format, guided either by a text prompt describing the concept or an input image depicting it. Our approach leverages score distillation sampling to optimize the parameters of a uniform rational B-spline (URBS) curve, ensuring that the drawing consists of a single continuous stroke by design. This representation provides fine-grained control over the level of detail, while additional loss terms allow us to steer the final artistic style. We demonstrate that our method outperforms state-of-the-art text-to-image models and optimization pipelines for this task, producing results that are both more aesthetically pleasing and more faithful to the style of continuous line drawing artists. Furthermore, because our method generates a vectorized curve, it directly supports downstream fabrication processes such as embroidery, laser engraving and wire bending.
Acknowledgments
We are grateful to the anonymous reviewers for their constructive suggestions. We also thank Danielle
Luterbacher for her assistance with the embroidery process. This work was supported in part by the
European Research Council (ERC) under the European Union's Horizon 2020 Research and Innovation
Programme (ERC Consolidator Grant, agreement No. 101003104, MYCLOTH). Open access publishing facilitated
by Eidgenossische Technische Hochschule Zurich, as part of the Wiley - Eidgenossische Technische
Hochschule Zurich agreement via the Consortium Of Swiss Academic Libraries.
Figure 2 of the main paper presents a drawing created by Felix Hornung, which can be licensed from
https://fhornung.net/sld.
Citation
@article{Magne:SLDgen:2026,
title = {Single Line Drawing Generation via Semantics-Driven Optimization},
author = {Magne, Tanguy and Binninger, Alexandre and Wiersma, Ruben and Sorkine-Hornung, Olga},
journal = {Computer Graphics Forum},
volume = {n/a},
number = {n/a},
pages = {e70502},
year = {2026},
doi = {https://doi.org/10.1111/cgf.70502},
}