Multimodal Detection of Unknown Objects on Roads for Autonomous Driving

@article{Bogdoll2022MultimodalDO,
  title={Multimodal Detection of Unknown Objects on Roads for Autonomous Driving},
  author={Daniel Bogdoll and Enrico Eisen and Maximilian Nitsche and Christin Scheib and Johann Marius Z{\"o}llner},
  journal={ArXiv},
  year={2022},
  volume={abs/2205.01414}
}
—Tremendous progress in deep learning over the last years has led towards a future with autonomous vehicles on our roads. Nevertheless, the performance of their perception systems is strongly dependent on the quality of the utilized training data. As these usually only cover a fraction of all object classes an autonomous driving system will face, such systems struggle with handling the unexpected. In order to safely operate on public roads, the identification of objects from unknown classes… 

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