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Erweiterte Realität

Publikationen

Seite 1 von 1.

  1. Learned Fusion: 3D Object Detection using Calibration-Free Transformer Feature Fusion

    In: Proceedings of the 13th International Conference on Pattern Recognition Applications and Methods. International Conference on Pattern Recognition …

  2. Thomas Stauner; Frédérik Blank; David Michael Fürst; Johannes Günther; Korbinian Hagn; Philipp Heidenreich; Markus Huber; Bastian Knerr; Thomas Schulik; Karl-Ferdinand Leiß

    SynPeDS: A Synthetic Dataset for Pedestrian Detection in Urban Traffic Scenes

    In: Proceedings of the 6th ACM Computer Science in Cars Symposium. ACM Computer Science in Cars Symposium (CSCS-2022), ACM, 12/2022.

  3. Object Permanence in Object Detection Leveraging Temporal Priors at Inference Time

    In: 2022 26th International Conference on Pattern Recognition (ICPR). International Conference on Pattern Recognition (ICPR-2022), August 21-25, …

  4. David Michael Fürst; Shriya T. P. Gupta; René Schuster; Oliver Wasenmüller; Didier Stricker

    HPERL: 3D Human Pose Estimation from RGB and LiDAR

    In: International Conference on Pattern Recognition. International Conference on Pattern Recognition (ICPR-2020), January 10-15, Milan, Italy, IEEE, …

  5. LRPD: Long Range 3D Pedestrian Detection Leveraging Specific Strengths of LiDAR and RGB

    In: IEEE International Conference on Intelligent Transportation Systems (ITSC). IEEE Intelligent Transportation Systems Conference (IEEE ITSC-2020), …

  6. Michael Weber; David Michael Fürst; J. Marius Zöllner

    Automated Focal Loss for Image based Object Detection

    In: 2020 IEEE Intelligent Vehicles Symposium (IV). IEEE Intelligent Vehicles Symposium (IV-2020), IEEE, 2020.

  7. Michael Weber; David Michael Fürst; J. Marius Zöllner

    Direct 3D Detection of Vehicles in Monocular Images with a CNN Based 3D Decoder

    In: 2019 IEEE Intelligent Vehicles Symposium (IV). IEEE Intelligent Vehicles Symposium (IV-2019), IEEE, 2019.

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Deutsches Forschungszentrum für
Künstliche Intelligenz GmbH (DFKI)
Forschungsbereich Erweiterte Realität
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