Deep Vectorization of Technical Drawings

Abstract

We present a new method for vectorization of technical line drawings, such as floor plans, architectural drawings, and 2D CAD images. Our method includes (1) a deep learning-based cleaning stage to eliminate the background and imperfections in the image and fill in missing parts, (2) a transformer-based network to estimate vector primitives, and (3) optimization procedure to obtain the final primitive configurations. We train the networks on synthetic data, renderings of vector line drawings, and manually vectorized scans of line drawings. Our method quantitatively and qualitatively outperforms a number of existing techniques on a collection of representative technical drawings.

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Fulltext PDF: Deep Vectorization of Technical Drawings
Supplementary PDF: Deep Vectorization of Technical Drawings Supplementary Materials
Source code: https://github.com/Vahe1994/Deep-Vectorization-of-Technical-Drawings
Video Video
Slides: Slides

Citing:

@inproceedings{2020-deep-vectorization,
 author = {Egiazarian, Vage and Voynov, Oleg and Artemov, Alexey and Volkhonskiy, Denis and Safin, Aleksandr and Taktasheva, Maria and Zorin, Denis and Burnaev, Evgeny},
 booktitle = {European Conference on Computer Vision},
 organization = {Springer},
 pages = {582--598},
 title = {Deep vectorization of technical drawings},
 year = {2020}
}

Vage Egiazarian	Oleg Voynov	Alexey Artemov	Denis Volkhonskiy
Aleksandr Safin	Maria Taktasheva	Denis Zorin	Evgeny Burnaev

Deep Vectorization of Technical Drawings

Abstract

Video

Resources