1 code implementation • ICCV 2023 • Shuxiao Ding, Eike Rehder, Lukas Schneider, Marius Cordts, Juergen Gall
Tracking 3D objects accurately and consistently is crucial for autonomous vehicles, enabling more reliable downstream tasks such as trajectory prediction and motion planning.
1 code implementation • 19 Jun 2023 • Peizheng Li, Shuxiao Ding, Xieyuanli Chen, Niklas Hanselmann, Marius Cordts, Juergen Gall
Accurately perceiving instances and predicting their future motion are key tasks for autonomous vehicles, enabling them to navigate safely in complex urban traffic.
no code implementations • 23 Nov 2022 • Philip de Rijk, Lukas Schneider, Marius Cordts, Dariu M. Gavrila
Knowledge Distillation (KD) is a well-known training paradigm in deep neural networks where knowledge acquired by a large teacher model is transferred to a small student.
1 code implementation • 14 Jun 2020 • Nils Gählert, Nicolas Jourdan, Marius Cordts, Uwe Franke, Joachim Denzler
In addition, we complement the Cityscapes benchmark suite with 3D vehicle detection based on the new annotations as well as metrics presented in this work.
no code implementations • 2 Apr 2017 • Marius Cordts, Timo Rehfeld, Lukas Schneider, David Pfeiffer, Markus Enzweiler, Stefan Roth, Marc Pollefeys, Uwe Franke
We believe this challenge should be faced by introducing a representation of the sensory data that provides compressed and structured access to all relevant visual content of the scene.
no code implementations • 18 Apr 2016 • Jonas Uhrig, Marius Cordts, Uwe Franke, Thomas Brox
Recent approaches for instance-aware semantic labeling have augmented convolutional neural networks (CNNs) with complex multi-task architectures or computationally expensive graphical models.
2 code implementations • CVPR 2016 • Marius Cordts, Mohamed Omran, Sebastian Ramos, Timo Rehfeld, Markus Enzweiler, Rodrigo Benenson, Uwe Franke, Stefan Roth, Bernt Schiele
Visual understanding of complex urban street scenes is an enabling factor for a wide range of applications.
no code implementations • 21 Mar 2016 • Martijn Arts, Marius Cordts, Monika Gorin, Marc Spehr, Rudolf Mathar
It is shown that the presented network converges to equilibrium points which are solutions to general non-negative least squares optimization problems.