David Michael Fürst
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Michael Fürst received a master degree in Computer Science at Karlsruhe Institute of Technology (KIT).
His bachelor thesis on Graph-SLAM in urban canyons and the master thesis on direct 3D car detection from monocular images using CNNs were done at Forschumszentrum Informatik (FZI).
In 2019 he joined the Augmented Vision Department of the German Research Center for Artificial Intelligence where he is currently focussing his research on Pedestrian Detection and Pose Estimation algorithms for automotive applications.
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 Applications and Methods (ICPRAM-2024), February 24-26, Rome, Italy, SCITEPRESS, 2024.
Object Permanence in Object Detection Leveraging Temporal Priors at Inference Time
ernational Conference on Pattern Recognition (ICPR-2022) August 21-25 Montreal Quebec Canada IEEE 2022 .
HPERL: 3D Human Pose Estimation from RGB and LiDAR
International Conference on Pattern Recognition. International Conference on Pattern Recognition (ICPR-2020) January 10-15 Milan Italy IEEE 2021 .
LRPD: Long Range 3D Pedestrian Detection Leveraging Specific Strengths of LiDAR and RGB
IEEE International Conference on Intelligent Transportation Systems (ITSC). IEEE Intelligent Transportation Systems Conference (IEEE ITSC-2020) September 20-23 Virtual Conference Greece IEEE 2020 .