End-to-End Wireframe Parsing

Yichao Zhou, Haozhi Qi, Yi Ma; The IEEE International Conference on Computer Vision (ICCV), 2019, pp. 962-971

Abstract


We present a conceptually simple yet effective algorithm to detect wireframes in a given image. Compared to the previous methods which first predict an intermediate heat map and then extract straight lines with heuristic algorithms, our method is end-to-end trainable and can directly output a vectorized wireframe that contains semantically meaningful and geometrically salient junctions and lines. To better understand the quality of the outputs, we propose a new metric for wireframe evaluation that penalizes overlapped line segments and incorrect line connectivities. We conduct extensive experiments and show that our method significantly outperforms the previous state-of-the-art wireframe and line extraction algorithms. We hope our simple approach can be served as a baseline for future wireframe parsing studies. Code has been made publicly available at https://github.com/zhou13/lcnn.

Related Material


[pdf] [supp]
[bibtex]
@InProceedings{Zhou_2019_ICCV,
author = {Zhou, Yichao and Qi, Haozhi and Ma, Yi},
title = {End-to-End Wireframe Parsing},
booktitle = {The IEEE International Conference on Computer Vision (ICCV)},
month = {October},
year = {2019}
}