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Dr.-Ing. Christian Müller

Organizational unit Agents and Simulated Reality
Contact +49 681 85775 4823 (Saarbrücken)

Address (Saarbrücken) Gebäude D3 2Stuhlsatzenhausweg 3D-66123 Saarbrücken

Publications

Reliable Student: Addressing Noise in Semi-Supervised 3D Object Detection

Farzad Nozarian; Shashank Agarwal; Farzaneh Rezaeianaran; Danish Shahzad; Atanas Poibrenski; Christian Müller; Philipp Slusallek

In: Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) Workshops. CVPR Workshop on Learning with Limited Labelled Data for Image and Video Understanding (L3D-IVU-2023), located at 2023 IEEE/CVF Conference on Computer Vision and Pattern Recognition, June 19, Vancouver, Canada, Pages 4981-4990, IEEE, 6/2023.

To the publication

Context-empowered Visual Attention Prediction in Pedestrian Scenarios

Igor Vozniak; Philipp Müller; Lorena Hell; Nils Lipp; Ahmed Abouelazm; Christian Müller

In: CVF. IEEE Winter Conference on Applications of Computer Vision (WACV-2023), January 4-6, Waikoloa, Hawaii, USA, Pages 950-960, IEEE Explore, IEEE Xplore, 1/2023.

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Uncertainty-aware pseudo labels for domain adaptation in pedestrian trajectory prediction

Atanas Poibrenski; Farzad Nozarian; Farzaneh Rezaeianaran; Christian Müller

In: IEEE ITSC-2023. IEEE Intelligent Transportation Systems Conference (IEEE ITSC-2023), September 24-28, Bilbao, Spain, IEEExplore, 2023.

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Profile

  • BERTHA

    BEhavioural Replication of Human drivers for CCAM

    The Horizon Europe project BERTHA kicked off on November 22nd-24th in Valencia, Spain. The project has been granted €7,981,799.50 from the European Commission to develop a Driver Behavioral Model…

    BERTHA

  • B5GCyberTestV2X

    Beyond 5G Virtuelle Umgebung für Cybersicherheitstests von V2X-Systeme

    The overall goal of the project is to enable safe and efficient autonomous driving by developing a virtual environment for cybersecurity testing of V2X systems in 5G and Beyond 5G scenarios…

    B5GCyberTestV2X

  • MOMENTUM

    Robust Learning with Hybrid AI for Trustworthy Interaction of Humans and Machines in Complex Environments

    MOMENTUM is a research project dedicated to TRUSTED-AI, which aims to advance the development and application of artificial intelligence by integrating robustness and explainability. The aim of the…

    MOMENTUM

  • BSI_SiKI2

    Studie: Sicherheit von KI-Systemen - TP 2: Symbolische und Hybride KI-Methoden

    The Federal Office for Information Security (BSI) has commissioned a study on the topic of "Security of AI systems: Symbolic and Hybrid AI Methods". The study records the current state of research of…

  • KAI

    AI-supported assistant for interior development

    Within the framework of the research project "AI-supported assistant for interior development" (KAI), a development tool is to be created that uses AI methods to support the developer in the…

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