YOLinO: Generic Single Shot Polyline Detection in Real Time

Abstract

The detection of polylines is usually either bound to branchless polylines or formulated in a recurrent way, prohibiting their use in real-time systems.We propose an approach that builds upon the idea of single shot object detection. Reformulating the problem of polyline detection as a bottom-up composition of small line segments allows to detect bounded, dashed and continuous polylines with a single head. This has several major advantages over previous methods. Not only is the method at 187 fps more than suited for real-time applications with virtually any restriction on the shapes of the detected polylines. By predicting multiple line segments for each cell, even branching or crossing polylines can be detected.We evaluate our approach on three different applications for road marking, lane border and center line detection. Hereby, we demonstrate the ability to generalize to different domains as well as both implicit and explicit polyline detection tasks.

Cite

Text

Meyer et al. "YOLinO: Generic Single Shot Polyline Detection in Real Time." IEEE/CVF International Conference on Computer Vision Workshops, 2021. doi:10.1109/ICCVW54120.2021.00326

Markdown

[Meyer et al. "YOLinO: Generic Single Shot Polyline Detection in Real Time." IEEE/CVF International Conference on Computer Vision Workshops, 2021.](https://mlanthology.org/iccvw/2021/meyer2021iccvw-yolino/) doi:10.1109/ICCVW54120.2021.00326

BibTeX

@inproceedings{meyer2021iccvw-yolino,
  title     = {{YOLinO: Generic Single Shot Polyline Detection in Real Time}},
  author    = {Meyer, Annika and Skudlik, Philipp and Pauls, Jan-Hendrik and Stiller, Christoph},
  booktitle = {IEEE/CVF International Conference on Computer Vision Workshops},
  year      = {2021},
  pages     = {2916-2925},
  doi       = {10.1109/ICCVW54120.2021.00326},
  url       = {https://mlanthology.org/iccvw/2021/meyer2021iccvw-yolino/}
}