  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.
