Timo Rehfeld — accepted AI-conference papers

2022

Hierarchical Road Topology Learning for Urban Mapless Driving

Li Zhang, Faezeh Tafazzoli, Gunther Krehl, Runsheng Xu, Timo Rehfeld, Manuel Schier +1

IROS 2022poster

The majority of current approaches in autonomous driving rely on High-Definition (HD) maps which detail the road geometry and surrounding area. Yet, this reliance is one of the obstacles to mass deployment of autonomous vehicles due to poor scalability of such prior maps. In this paper, we tackle th…

Cited by 14 Source ↗Scholar ↗

2016

The Cityscapes Dataset for Semantic Urban Scene Understanding

Marius Cordts, Mohamed Omran, Sebastian Ramos, Timo Rehfeld, Markus Enzweiler, Rodrigo Benenson +3

CVPR 2016spotlight

Visual understanding of complex urban street scenes is an enabling factor for a wide range of applications. Object detection has benefited enormously from large-scale datasets, especially in the context of deep learning. For semantic urban scene understanding, however, no current dataset adequately…

Cited by 15494 PDF ↗Scholar ↗