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YOLinO: Generic Single Shot Polyline Detection in Real Time

Meyer, Annika; Skudlik, Philipp; Pauls, Jan-Hendrik; Stiller, Christoph

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.


Zugehörige Institution(en) am KIT Institut für Mess- und Regelungstechnik mit Maschinenlaboratorium (MRT)
Publikationstyp Proceedingsbeitrag
Publikationsmonat/-jahr 10.2021
Sprache Englisch
Identifikator KITopen-ID: 1000139015
Erschienen in Proceedings of the IEEE/CVF International Conference on Computer Vision (ICCV) Workshops.
Veranstaltung IEEE/CVF International Conference on Computer Vision (ICCV 2021), Online, 11.10.2021 – 17.10.2021
Seiten 2916-2925
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